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KR Prior Art | Ground | Reference | Owner of the Reference | Title | Semantic Mapping | Basis | Anticipation | Challenged Claims |
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| 1 | WEB USAGE ANALYSIS AND USER PROFILING. 1836: 7-20 2000 (Murray, 2000) | SourceWorks Consulting Private Limited (India) | Inferring Demographic Attributes Of Anonymous Internet Users | ▪ category keywords ≈ demographic information ▪ search terms ≈ search terms | X | ||
| 2 | COMPUTER NETWORKS AND ISDN SYSTEMS. 30 (1-7): 107-117 APR 1998 (Brin, 1998) | Stanford University | The Anatomy Of A Large-scale Hypertextual Web Search Engine | ▪ search request ≈ search results ▪ search engine ≈ search engine | X | ||
| 3 | 2007 5TH IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS, VOLS 1-3. : 725-730 2007 (Espinoza, 2007) | Universidad de Zaragoza, Aragón (España) | Discovering Web Services Using Semantic Keywords | ▪ search engine ≈ Web service ▪ search terms ≈ user key | X | ||
| 4 | CA2624186A1 (Adam D. Smith, 2007) | (Original Assignee) Google Inc.; Adam D. Smith; Brian Singerman; Naga Sridhar Kataru (Current Assignee) Google LLC | Generation of topical subjects from alert search terms | ▪ search engine ≈ search engine ▪ search terms ≈ search terms ▪ category keywords ≈ more search | ▪ 35 U.S.C. 103(a) ▪ 35 U.S.C. 102(b) ▪ 35 U.S.C. 102(e) | ▪ teaches that the main website contains assets such as news weather stock prices sports scores etc which are shared… ▪ discloses allowing a user to specify whether a hyperlink should open within an existing browser window or a new browser… ▪ teaches after receiving content ie call to retrieve CRM contentpage… ▪ teaches the invention as claimed including a method of servicing a request for a document over a computer network… | X |
| 5 | CN101194256A (凯文·A·吉布斯, 2008) | (Original Assignee) 谷歌公司 | 具有表意文字和音标字符的语言的自动输入完成的方法和系统 | ▪ search terms ≈ 包括搜索 ▪ W ix ≈ 用于将由 | ▪ 35 U.S.C. 103(a) ▪ 35 U.S.C. 102(b) | ▪ teaches an example of user pressing some keys and a list of propose words is presented and is considered operating in… ▪ discloses wherein the executable instructions further comprise executable instructions to generate the set of page state… ▪ discloses a system for enriching input text with missing information but does not specifically teach a system being… ▪ teaches obtaining a set of predicted complete queries include instructions for converting a respective partial search… | X |
| 6 | US20020107859A1 (Akemi Tsuyuki, 2002) | (Original Assignee) Tsuyuki Software Lab (Current Assignee) Tsuyuki Software Lab | Associating information management system, program for associating information management, and recording medium | ▪ search request ≈ setting condition ▪ search terms ≈ retrieval result | X | ||
| 7 | US20020152051A1 (Yoshio Fukushige, 2002) | (Original Assignee) Panasonic Corp (Current Assignee) Panasonic Corp | Text classifying parameter generator and a text classifier using the generated parameter | ▪ category X ≈ evaluation values ▪ ranking categories ≈ descending order ▪ ∑ j ≈ said list | ▪ 35 U.S.C. 103(a) ▪ 35 U.S.C. 102(b) ▪ 35 U.S.C. 102(e) | ▪ teaches a GUI for display within a touch screen display of a handheld device wherein the handheld device is configured… ▪ teaches a patient monitoring system as previously explained but does not expressly disclose that the patient monitor… ▪ teaches a method including recommending one or more lab tests based at least in part upon the prescription see column… ▪ discloses a method of presenting medical records for use by a medical provider comprising col… | X |
| 8 | US7146416B1 (Janet Yoo, 2006) | (Original Assignee) Yahoo Inc (Current Assignee) ENERGETIC POWER INVESTMENT Ltd | Web site activity monitoring system with tracking by categories and terms | ▪ category keywords ≈ demographic information ▪ search request ≈ search request, search results | X | ||
| 9 | CN101140588A (舒琦, 2008) | (Original Assignee) 华为技术有限公司 | 一种关联关系搜索结果的排序方法及装置 | ▪ ranking categories ≈ 排序模块 ▪ N W ij ≈ 的集合 | X | ||
| 10 | CN101159730A (伍志勇, 2008) | (Original Assignee) 华为技术有限公司 | 多媒体联络中心处理信息的方法、系统及装置 | ▪ search request ≈ 搜索数据 ▪ relationship Issue ≈ 对应关系 | ▪ 35 U.S.C. 103(a) ▪ 35 U.S.C. 102(e) | ▪ teaches wherein the lowlevel descriptor language is extensible markup language XML column… ▪ discloses a system and method for facilitating the exchange of information between human users in a networkedcomputer… ▪ discloses automatic inspection of content of data messages text messages and emails column… ▪ discloses all the aspect of the claimed invention as set forth above but fails to teach the telephony devices is a hunt… | X |
| 11 | US20080059308A1 (David Gerken, 2008) | (Original Assignee) BUZZDASH Inc (Current Assignee) Tribune Interactive Inc | Methods and apparatus for using poll results to target and/or select advertisements | ▪ search request ≈ selecting advertisements ▪ ranking categories, search engine ≈ collaborative filtering | ▪ 35 U.S.C. 103(a) ▪ 35 U.S.C. 102(e) | ▪ teaches the advertising server getting a code from the user device that the ad has been viewed and the indicator has… ▪ discloses inserting ad listing into an affiliate content page see… ▪ discloses all the subject matters of the claimed invention concept… ▪ discloses that the community messaging application that takes the user s surveypoll real time can be a standalone… | X |
| 12 | US20080016101A1 (Adam Ginsburg, 2008) | (Original Assignee) Shopping com (Current Assignee) eBay Inc ; Shopping com | Systems and methods for dynamically updating relevance of a selected item | ▪ Rank ≈ providing rank ▪ N W ij ≈ n storage | ▪ 35 U.S.C. 103(a) ▪ 35 U.S.C. 102(e) ▪ 35 U.S.C. 102(b) | ▪ discloses wherein the digital information comprises a database having a structural relationship among the nodes defined… ▪ teaches allowing a user to search music based on music title… ▪ discloses a globaltokeyword weighting scheme global node rank information as disclose in… ▪ discloses i ndices evolve at least in part by providing subsequent users with summary comparison usage information based… | X |
| 13 | EP1862922A1 (Marko Degenkolb, 2007) | (Original Assignee) SAP SE (Current Assignee) SAP SE | System and method for searching web services and generating a search index | ▪ search request ≈ search results ▪ search engine ≈ Web service | X | ||
| 14 | CN101067807A (骆祥峰, 2007) | (Original Assignee) 上海大学 | 文本语义的可视化表示与获取方法 | ▪ category keywords ≈ 关键词对 ▪ N W ij ≈ 的集合 | X | ||
| 15 | WO2007115254A2 (Sean M. Quinlan, 2007) | (Original Assignee) Visto Corporation | System and method for searching disparate datastores via a remote device | ▪ search request ≈ search results ▪ search engine ≈ search engine | X | ||
| 16 | US20070288433A1 (Raghav Gupta, 2007) | (Original Assignee) eBay Inc (Current Assignee) eBay Inc | Determining relevancy and desirability of terms | ▪ category keywords ≈ extracted keyword ▪ search request ≈ search results | X | ||
| 17 | WO2007106269A1 (Yevgeny E. Agichtein, 2007) | (Original Assignee) Microsoft Corporation | Mining web search user behavior to enhance web search relevance | ▪ search request ≈ search results ▪ search engine ≈ search engine | X | ||
| 18 | CN101110074A (张明, 2008) | (Original Assignee) 浪潮乐金信息系统有限公司 | 基于文件系统缓存的数据加速查询方法 | ▪ search engine ≈ 文件检索 ▪ relationship Issue ≈ 对应关系 | X | ||
| 19 | US20070174257A1 (Bruce Thomas Howard, 2007) | (Original Assignee) ROXSE LLC (Current Assignee) ROXSE LLC | Systems and methods for providing sorted search results | ▪ search request ≈ search request ▪ search engine ≈ search engine ▪ video clips ≈ audio file | X | ||
| 20 | US20070156669A1 (Giovanni Marchisio, 2007) | (Original Assignee) Insightful Corp (Current Assignee) Fiver LLC | Extending keyword searching to syntactically and semantically annotated data | ▪ search engine ≈ specific relationship, search engine ▪ search request ≈ search results ▪ search terms ≈ result data | X | ||
| 21 | US20080140616A1 (Nicolas Encina, 2008) | (Original Assignee) Praxeon Inc (Current Assignee) Praxeon Inc | Document processing | ▪ search request ≈ search results ▪ search engine ≈ search engine | X | ||
| 22 | US20070136236A1 (Timo Kussmaul, 2007) | (Original Assignee) International Business Machines Corp (Current Assignee) International Business Machines Corp | Service Broker Realizing Structuring of Portlet Services | ▪ search request ≈ search request ▪ search engine ≈ Web service | X | ||
| 23 | CN101097573A (杨海松, 2008) | (Original Assignee) 腾讯科技（深圳）有限公司 | 一种自动问答系统及方法 | ▪ category keywords ≈ 一个关键词 ▪ relationship Issue ≈ 对应关系 | X | ||
| 24 | US20060218111A1 (Hunter Cohen, 2006) | (Original Assignee) Cohen Hunter C | Filtered search results | ▪ search request ≈ search results ▪ Rank ≈ red display | X | ||
| 25 | JP2007233874A (Tatsumi Mashita, 2007) | (Original Assignee) Nomura Research Institute Ltd; 株式会社野村総合研究所 | 投稿処理装置 | ▪ search request ≈ の要求 ▪ video clips ≈ の質問 | X | ||
| 26 | US20060129550A1 (Hongyuan Zha, 2006) | (Original Assignee) Hongyuan Zha; Sean Suchter (Current Assignee) R2 Solutions LLC ; Altaba Inc | Associating documents with classifications and ranking documents based on classification weights | ▪ N W, N W ij ≈ intermediate values ▪ ∑ j ≈ said list | ▪ 35 U.S.C. 103(a) ▪ 35 U.S.C. 102(b) ▪ 35 U.S.C. 102(e) | ▪ discloses a method and apparatus for facilitating and controlling a buyer driven market where prospective buyers of… ▪ discloses signaling the solicitor that a contract cannot be formed col… ▪ discloses receiving a request for withdrawal of an offer and retracting the offer via deleting the offer in question… ▪ discloses indexing media content on the internet comprising a mediax file containing a hierarchy of metadata however… | X |
| 27 | US20060080303A1 (Antony Sargent, 2006) | (Original Assignee) Computer Associates Think Inc (Current Assignee) Google LLC | Method, apparatus, and computer program product for indexing, synchronizing and searching digital data | ▪ ranking categories ≈ outputting step ▪ search terms ≈ search terms ▪ category keywords ≈ more search | X | ||
| 28 | JP2006202253A (Takashi Fujimura, 2006) | (Original Assignee) Nippon Telegr & Teleph Corp <Ntt>; 日本電信電話株式会社 | 情報評価装置、コンテンツ検索装置、情報評価方法、コンテンツ検索方法、それらのプログラム及び記録媒体 | ▪ relationship Issue ≈ コンテンツサーバ装置, の関係 ▪ search engine ≈ 検索方法, 検索手段 | X | ||
| 29 | US20060161543A1 (Xiao Feng, 2006) | (Original Assignee) Tiny Engine Inc (Current Assignee) Tiny Engine Inc | Systems and methods for providing search results based on linguistic analysis | ▪ search terms ≈ search parameters ▪ search engine ≈ search engine | X | ||
| 30 | US20060106788A1 (Brady Forrest, 2006) | (Original Assignee) Microsoft Corp (Current Assignee) Microsoft Technology Licensing LLC | Computer-implemented system and method for providing authoritative answers to a general information search | ▪ search request ≈ search results ▪ search engine ≈ search engine ▪ relationship Issue ≈ first member ▪ ∑ j ≈ said list | ▪ 35 U.S.C. 102(a) | ▪ teaches that a compound enhancing phagocytosis of target cells is also useful in treating cancer… | X |
| 31 | US20050256866A1 (Qi Lu, 2005) | (Original Assignee) Yahoo Inc (Current Assignee) Altaba Inc ; Slack Technologies Inc | Search system and methods with integration of user annotations from a trust network | ▪ relationship Issue ≈ report information ▪ search request ≈ search results | X | ||
| 32 | EP1557773A2 (Oliver Hurst-Hiller, 2005) | (Original Assignee) Microsoft Corp (Current Assignee) Microsoft Corp | System and method for searching disparate resources | ▪ search request ≈ search request ▪ search terms ≈ search terms | ▪ 35 U.S.C. 103(a) ▪ 35 U.S.C. 102(b) ▪ 35 U.S.C. 102(e) | ▪ teaches of providing a set of recommended search queries when the search result is null or empty col… ▪ teaches generating a rank value for each keyword the higher the rank value the top position the keyword will list and… ▪ teaches a method for creating a plurality of web pages to provide a user s product information to remote entities… ▪ teaches possible examples of the input device a keyboard microphone touch screen or a mouse see column… | X |
| 33 | CN1716244A (梁平, 2006) | (Original Assignee) 西安迪戈科技有限责任公司 | 智能搜索、智能文件系统和自动智能助手的方法 | ▪ search terms ≈ 包括搜索 ▪ relationship Issue ≈ 相关关系 ▪ N W, N ≈ 式进行 ▪ N W ij ≈ 的集合 | X | ||
| 34 | US20050108200A1 (Frank Meik, 2005) | (Original Assignee) COGISUM INTERMEDIA AG (Current Assignee) COGISUM INTERMEDIA AG | Category based, extensible and interactive system for document retrieval | ▪ category X ≈ different categories ▪ search request ≈ search results ▪ search engine ≈ search engine ▪ search terms ≈ search terms, data space | X | ||
| 35 | US20060080292A1 (Faisal Saud Alanzi, 2006) | (Original Assignee) DAR AL RIYADH HOLDING Co Ltd (Current Assignee) DAR AL RIYADH HOLDING Co Ltd | Enhanced interface utility for web-based searching | ▪ search request ≈ search results ▪ ∑ i ≈ different one ▪ search engine ≈ search engine ▪ search terms ≈ search terms | X | ||
| 36 | US20050120006A1 (Timothy Nye, 2005) | (Original Assignee) Geosign Corp (Current Assignee) TrueLocal Inc | Systems and methods for enhancing web-based searching | ▪ ranking categories, category keywords ≈ more categories ▪ search request ≈ search request, search results ▪ search engine ≈ search engine | X | ||
| 37 | US7386542B2 (Mark T. Maybury, 2008) | (Original Assignee) Mitre Corp (Current Assignee) OAKHAM TECHNOLOGIES LLC | Personalized broadcast news navigator | ▪ search terms ≈ search terms ▪ video clips ≈ video clip | X | ||
| 38 | US20050076003A1 (Paul DuBose, 2005) | (Original Assignee) ADAPTIVE SEARCH LLC (Current Assignee) ADAPTIVE SEARCH LLC | Method and apparatus for delivering personalized search results | ▪ search engine ≈ search engine ▪ search terms ≈ search terms | X | ||
| 39 | US20050240580A1 (Oren Zamir, 2005) | (Original Assignee) Google LLC (Current Assignee) Google LLC | Personalization of placed content ordering in search results | ▪ search request ≈ search results ▪ search engine ≈ search engine | ▪ 35 U.S.C. 103(a) ▪ 35 U.S.C. 102(b) ▪ 35 U.S.C. 102(e) | ▪ teaches the search interface and affinity engine for generating a list of similar users and displaying an identifier… ▪ discloses the user activity includes a content message telescoping request… ▪ teaches a method and computer readable medium comprising software code configured to implement functions comprising… ▪ discloses that implicit profile information is obtained through analyzing the user s status information that includes… | X |
| 40 | US20050283468A1 (Sepandar Kamvar, 2005) | (Original Assignee) Google LLC (Current Assignee) Google LLC | Anticipated query generation and processing in a search engine | ▪ search terms ≈ search terms ▪ category keywords ≈ more search | X | ||
| 41 | WO2004111771A2 (Krishna Bharat, 2004) | (Original Assignee) Google, Inc. | Serving advertisements using user request information and user information | ▪ category keywords ≈ demographic information ▪ search engine ≈ search engine | ▪ 35 U.S.C. 103(a) ▪ 35 U.S.C. 102(b) ▪ 35 U.S.C. 102(e) | ▪ discloses a system for presenting mobile communication facility data to a first and a second bidder in real time the… ▪ teaches systems and methods for assessing the bid values for placement of content such as advertisements in a certain… ▪ teaches creating an association between the selection of the user and the indication of information desired by the… ▪ teaches the claimed limitations wherein the media content is produced by the mobile device and comprises one or more… | X |
| 42 | US20030217052A1 (Tal Rubenczyk, 2003) | (Original Assignee) Celebros Ltd (Current Assignee) Celebros Ltd | Search engine method and apparatus | ▪ N W, relationship Issue ≈ following relationships, then c ▪ search terms ≈ search terms | X | ||
| 43 | US20040220902A1 (Stephen Gates, 2004) | (Original Assignee) International Business Machines Corp (Current Assignee) International Business Machines Corp | System and method for generating refinement categories for a set of search results | ▪ ranking categories ≈ ranking categories ▪ search request ≈ search results ▪ ∑ i, ix ∑ i ≈ steps i | ▪ 35 U.S.C. 103(a) ▪ 35 U.S.C. 102(b) ▪ 35 U.S.C. 102(e) | ▪ teaches the invention substantially as claimed and described in claim… ▪ teaches generating a rank value for each keyword the higher the rank value the top position the keyword will list and… ▪ discloses that the user may explicitly enter music items and ratings or the system may derive implicit ratings of music… ▪ teaches a client computer system including a method of operation as in claim… | X |
| 44 | US6963867B2 (James L. Ford, 2005) | (Original Assignee) A9 com Inc (Current Assignee) A9 com Inc | Search query processing to provide category-ranked presentation of search results | ▪ category X ≈ particular items ▪ search request ≈ search results ▪ search engine ≈ time window | X | ||
| 45 | US6816850B2 (Gary A. Culliss, 2004) | (Original Assignee) Ask Jeeves Inc (Current Assignee) IAC Search and Media Inc | Personalized search methods including combining index entries for catagories of personal data | ▪ search terms ≈ displaying results ▪ ranking categories, category keywords ≈ more categories | X | ||
| 46 | US20030088553A1 (Dante Monteverde, 2003) | (Original Assignee) Emergency 24 Inc (Current Assignee) Emergency 24 Inc | Method for providing relevant search results based on an initial online search query | ▪ search request ≈ search results ▪ search terms ≈ search terms | X | ||
| 47 | US7043492B1 (Michael Renn Neal, 2006) | (Original Assignee) Requisite Technology Inc (Current Assignee) International Business Machines Corp | Automated classification of items using classification mappings | ▪ search terms ≈ higher hierarchical level ▪ search engine ≈ search engine | X | ||
| 48 | US20020120609A1 (Andrew Lang, 2002) | (Original Assignee) Lang Andrew K.; Kosak Donald M. (Current Assignee) I/P Engine Inc | Collaborative/adaptive search engine | ▪ search request ≈ search results ▪ search engine ≈ search engine | ▪ 35 U.S.C. 103(a) ▪ 35 U.S.C. 102(b) ▪ 35 U.S.C. 102(e) | ▪ discloses all the claimed subject matter as set forth above in claim… ▪ teaches adaptive partitioning techniques in performing query request and routing… ▪ teaches a tangible computerreadable medium according to claim… ▪ discloses determining at least one resource responsive to the at least one keyword and responsive to information related… | X |
| 49 | US6738764B2 (Jianchang Mao, 2004) | (Original Assignee) Verity Inc (Current Assignee) Valtrus Innovations Ltd | Apparatus and method for adaptively ranking search results | ▪ search request ≈ search results ▪ search engine ≈ search engine | X | ||
| 50 | US6526440B1 (Krishna Bharat, 2003) | (Original Assignee) Google LLC (Current Assignee) Google LLC | Ranking search results by reranking the results based on local inter-connectivity | ▪ search terms ≈ search terms ▪ N W, N W ij ≈ ∑ i | ▪ 35 U.S.C. 103(a) ▪ 35 U.S.C. 102(b) ▪ 35 U.S.C. 102(e) | ▪ teaches a method of ranking article identifiers of a result set from an implicit query implied from a user s current… ▪ teaches A method for enabling users searching for common subject matter… ▪ teaches a query system using natural language processing techniques to improve search results… ▪ discloses the claimed invention but fails to disclose based on an evaluation of item information that is included in the… | X |
| 51 | US6658423B1 (William Pugh, 2003) | (Original Assignee) Google LLC (Current Assignee) Google LLC | Detecting duplicate and near-duplicate files | ▪ search request ≈ search results ▪ N W, N ≈ then c | ▪ 35 U.S.C. 103(a) ▪ 35 U.S.C. 102(e) ▪ 35 U.S.C. 102(b) | ▪ discloses the limitations substantially similar to those in claim… ▪ teaches allowing a user to search music based on music title… ▪ discloses i ndices evolve at least in part by providing subsequent users with summary comparison usage information based… ▪ teaches the extraction of parts of documents such as words etc for generating ngerprints… | X |
| 52 | US6539377B1 (Gary A. Culliss, 2003) | (Original Assignee) Ask Jeeves Inc (Current Assignee) IAC Search and Media Inc | Personalized search methods | ▪ category X ≈ different categories ▪ search request ≈ search results | ▪ 35 U.S.C. 103(a) ▪ 35 U.S.C. 102(b) ▪ 35 U.S.C. 102(e) | ▪ teaches user interface and other enhancements for natural language information retrieval system and method… ▪ teaches generation of enlarged participatory broadcast audience… ▪ teaches the claimed limitations parsing the query breaking the query into the query terms as col… ▪ teaches all the claimed subject matter as discussed above with respect to claim… | X |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | WEB USAGE ANALYSIS AND USER PROFILING. 1836: 7-20 2000 Publication Year: 2000 Inferring Demographic Attributes Of Anonymous Internet Users SourceWorks Consulting Private Limited (India) Murray, Durrell, Masand, Spiliopoulou |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords (demographic information) with search terms (search terms) in a search request provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
Inferring Demographic Attributes Of Anonymous Internet Users . Today it is quite common for web page content to include an advertisement . Since advertisers often want to target their message to people with certain demographic attributes , the anonymity of Internet users poses a special problem for them . The purpose of the present research is to find an effective way to infer demographic information (category keywords) (e . g . gender , age or income) about people who use the Internet but for whom demographic information is not otherwise available . Our hope is to build a high quality database of demographic profiles covering a large segment of the Internet population without having to survey each individual Internet user . Though Internet users are largely anonymous , they nonetheless provide a certain amount of usage information . Usage information includes , but is not limited to , (a) search terms (search terms) entered by the Internet user and (b) web pages accessed by the Internet user . In this paper , we describe an application of the Latent Semantic Analysis (LSA) [1] information retrieval technique to construct a vector space in which we can represent the usage data associated with each Internet user of interest . Subsequently , we show how the LSA vector space enables us to produce demographic inferences by supplying the input to a three layer neural model trained using the scaled conjugate gradient (SCG) method . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | COMPUTER NETWORKS AND ISDN SYSTEMS. 30 (1-7): 107-117 APR 1998 Publication Year: 1998 The Anatomy Of A Large-scale Hypertextual Web Search Engine Stanford University Brin, Page |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine (search engine) identifying relevant categories based upon a comparison of category keywords with search terms in a search request (search results) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
The Anatomy Of A Large-scale Hypertextual Web Search Engine . In this paper , we present Google , a prototype of a large-scale search engine (search engine) which makes heavy use of the structure present in hypertext . Google is designed to crawl and index the Web efficiently and produce much more satisfying search results (search request) than existing systems . The prototype with a full text and hyperlink database of at least 24 million pages is available at http : //google . stanford . edu/ To engineer a search engine is a challenging task . Search engines index tens to hundreds of millions of Web pages involving a comparable number of distinct terms . They answer tens of millions of queries every day . Despite the importance of large-scale search engines on the Web , very little academic research has been done on them . Furthermore , due to rapid advance in technology and Web proliferation , creating a Web search engine today is very different from three years ago . This paper provides an in-depth description of our large-scale Web search engine - the first such detailed public description we know of to date . Apart from the problems of scaling traditional search techniques to data of this magnitude , there are new technical challenges involved with using the additional information present in hypertext to produce better search results . This paper addresses this question of how to build a practical large-scale system which can exploit the additional information present in hypertext . Also we look at the problem of how to effectively deal with uncontrolled hypertext collections where anyone can publish anything they want . (C) 1998 Published by Elsevier Science B . V . All rights reserved . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | 2007 5TH IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS, VOLS 1-3. : 725-730 2007 Publication Year: 2007 Discovering Web Services Using Semantic Keywords Universidad de Zaragoza, Aragón (España) Espinoza, Mena, Ieee |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine (Web service) identifying relevant categories based upon a comparison of category keywords with search terms (user key) in a search request provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
Discovering Web Services Using Semantic Keywords . With the increasing growth in popularity of Web service (search engine) s , the discovery of relevant services becomes a significant challenge . In order to enhance the service discovery is necessary that both the web service description and the request for discovering a service explicitly declare their semantics . Some languages and frameworks have been developed to support rich semantic service descriptions and discover using ontology concepts . However , the manual creation of such concepts is tedious and error-prone and many users accustomed to automatic tools might not want to invert his time in obtaining this knowledge . In this paper we propose a system that assists to both service producers and service consumers in the discovery of semantic keywords which can be used to describe and discover web services respectively . First , our system enhances semantically the list of keywords extracted from the elements that comprise the description of a web service and the user key (search terms) words used for discover a service . Second , an ontology matching process is used to discovers matchings between the ontological terms of a service description and a request for service selection . Third , a subsumption reasoning algorithm tries to find service description(s) which match the user request . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | CA2624186A1 Filed: 2006-09-27 Issued: 2007-04-05 Generation of topical subjects from alert search terms (Original Assignee) Google Inc.; Adam D. Smith; Brian Singerman; Naga Sridhar Kataru (Current Assignee) Google LLC Adam D. Smith, Brian Singerman, Naga Sridhar Kataru |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine (search engine) identifying relevant categories based upon a comparison of category keywords (more search) with search terms (search terms) in a search request provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
CA2624186A1 CLAIM 3 . The method of claim 2 , wherein receiving the registration request further includes : receiving one or more search terms (search terms) that define a subject of the email alert . CA2624186A1 CLAIM 10 . The method of claim 1 , further comprising : using the identified topical subjects in ranking documents returned from a search engine (search engine) . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | CN101194256A Filed: 2005-10-11 Issued: 2008-06-04 具有表意文字和音标字符的语言的自动输入完成的方法和系统 (Original Assignee) 谷歌公司 凯文·A·吉布斯 |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords with search terms (包括搜索) in a search request provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix (用于将由) ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
CN101194256A CLAIM 9 . 如权利要求2所述的方法，其中所述集包括搜索 (search terms) 査询和至少一 个URL。 CN101194256A CLAIM 56 . 如权利要求52所述的计算机程序产品，还包括： 用于将由 (W ix) 用户群体提交的査询包括在该预测查询集中的指令。 |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20020107859A1 Filed: 2002-01-14 Issued: 2002-08-08 Associating information management system, program for associating information management, and recording medium (Original Assignee) Tsuyuki Software Lab (Current Assignee) Tsuyuki Software Lab Akemi Tsuyuki |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords with search terms (retrieval result) in a search request (setting condition) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20020107859A1 CLAIM 19 . An associating information management system , comprising : a member management table for storing member information of individuals and organizations including name or organization name , address , telephone number , etc . ; said system records relationship record defining relationship between a member registered in the member management table and another member relating to said member by parent-child relationship , said system being provided with a database , which comprises a relationship management table for recording classification code indicating type of the relationship and priority rank of the relationship , and said system extracts up to any degree of relative as desired and displays whether a relationship route is made up using member codes of two members as set to the reference person , said system further comprising means for executing the steps of : (1) setting one of the two members for tracing the relationship as a regular member , and the other as a sub-member , storing a setting condition (search request) to trace whether the sub-member is connected with the regular member , and initializing array area in the memory for temporarily storing retrieval result (search terms) ; (2) storing the setting condition as to up to which degree should be searched at the furthest or whether the shortest route should be searched or all routes should be searched as designated by the user when processing is performed ; (3) extracting the first degree member in parent-child relationship of the regular member ; (3-1) judging whether ia-th (i=1 to n) member is a sub-member or not among the number of records “na” of the extracted first degree member ; (3-1-1) if it is a sub-member , executing the processing of Step (3-1) to the record of the next first degree member by storing the route from the regular member in array area of the memory ; (4) if it is not a sub-member , extracting the second degree member in parent-child relationship of ia-th member of the first degree ; (4-1) judging whether ib-th (i=1 to n) member is a sub-member or not among the number of records “nb” of the second degree extracted ; (4-1-1) if it is a sub-member , executing the processing of Step (4-1) to the record of the next second degree by storing the route from the regular member in array area of the memory ; (4-2) if it is not a sub-member , judging whether the same member as ib-th member of the second degree is present at higher position in the route or not ; (4-2-1) if it is present at higher position , executing the processing of Step (4-1) to the record of the next second degree member by interrupting the processing ; (5) if it is not present at higher position , extracting the third degree member in parent-child relationship of ib-th member of the second degree ; (5-1) judging whether ic-th (i=1 to n) member is a sub-member or not among the number of records “nc” of the third degree extracted ; (5-1-1) if it is a sub-member , executing the processing of Step (5-1) to the record of the next third degree member by storing the route from the regular member in array area of the memory ; (5-2) if it is not a sub-member , judging whether the same member as ic-th member of the third degree is not present at higher position in the route or not ; (5-2-1) if it is present at higher position , interrupting the processing and executing the processing of Step (5-1) to the record of the next third degree member by interrupting the processing ; (6) if it not present at higher position , extracting the fourth degree member in parent-child relationship of ic-th member of the third degree ; (7) repeating the procedure by progressively increasing the value up to the degree of the number as set in advance , and performing the following processing in the final degree member : (7-1) judging whether ix-th (i=1 to n) member is a sub-member or not among the number of records “nx” of the final degree extracted ; (7-1-1) if it is a sub-member , storing the route from the regular member in array area of the memory , and advancing to the next record of the final degree ; (7-2) if it is not a sub-member , advancing to the next record of the final degree . If the record of the final degree is completed up to “n” , performing processing by progressively increasing by one the number of records of the degree one step before ; (7-3) if the number of recording of the degree one step before is completed up to “In” , performing processing by progressively increasing by one the number of records of the degree one step before ; (8) performing this procedure until the number of records of all degrees is completed ; (9) rearranging retrieval results stored in array area of the memory from the member of lower degree in the route ; (10) displaying the first of the retrieval results in the tree view area ; and (11) displaying the route selected by the user among the retrieval results in the tree view area if the user designates the change of the retrieval result display in the pulldown list box . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20020152051A1 Filed: 2001-12-28 Issued: 2002-10-17 Text classifying parameter generator and a text classifier using the generated parameter (Original Assignee) Panasonic Corp (Current Assignee) Panasonic Corp Yoshio Fukushige, Yuji Kanno, Yasuki Iizuka, Koichi Tamari |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories (descending order) , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords with search terms in a search request provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j (said list) = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X (evaluation values) ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20020152051A1 CLAIM 21 . A system as defined in claim 1 , further comprising : means , responsive to the operator selecting one of said set of documents , for calculating a degree of similarity to each of other documents of said set ; means for displaying a first list of documents whose membership scores indicate a nonmembership of said specified category in descending order (ranking categories) of the degree of similarity and a second list of documents whose membership scores indicate a membership of said specified category in ascending order of the degree of similarity . US20020152051A1 CLAIM 23 . A system as defined in claim 1 , further comprising : means for storing , for each category , a list of category IDs of categories whose membership scores should be set to a specific one of possible values of the membership score if said membership score of each category is evaluated to 1 , which indicates a membership of the category ; and means , operative in the event the membership score of a certain document is evaluated as 1 , for automatically setting the membership scores of the documents contained in said list (∑ j) associated with said certain document to said specific values . US20020152051A1 CLAIM 51 . A method of generating a set of parameters for use in determining whether a given document belongs to a specified one of a plurality of predetermined categories , the method comprising the steps of : preparing a set of documents , each document having an identifier (ID) ; preparing a document data set containing a record for each document which record contains a document ID of said document and a feature vector representing features of said document in a predefined vector space ; preparing a category data set containing a record for each category which record contains a category ID of said category , a category name and said set of parameters , said parameters including a reference vector representing features of said category in said predefined vector space and a threshold determined for said category ; calculating , for each document (or the document) , a membership score indicative of whether the document belongs to said specified category by using a feature vector of the document , a reference vector of said specified category and a threshold of said specified category ; supporting an operator to interactively enter various command parameters for selecting documents for which the calculated membership scores are to be evaluated ; in response to an input of one of said command parameters , visually presenting information useful for said selection of documents to said operator ; displaying selected documents and permitting said operator to enter an evaluation value to each of the displayed selected documents ; and reflecting said entered evaluation values (category X) to said reference vector of said specified category . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US7146416B1 Filed: 2000-09-01 Issued: 2006-12-05 Web site activity monitoring system with tracking by categories and terms (Original Assignee) Yahoo Inc (Current Assignee) ENERGETIC POWER INVESTMENT Ltd Janet Yoo, Kian-Tat Lim, Stanley Ben Wong, Elliott Yasnokvsky |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords (demographic information) with search terms in a search request (search request, search results) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US7146416B1 CLAIM 12 . The apparatus of claim 1 , further comprising a database with demographic information (category keywords) for at least a portion of the plurality of users , and wherein the statistics include statistics reflecting aggregate change in interest for each canonical term in a selected category for users having at least one selected demographic characteristic for which information exists in the database . US7146416B1 CLAIM 15 . The apparatus of claim 1 , wherein the events include a click stream input received from one of the plurality of users in response to search results (search request) provided to that user based on a canonical term , and the categorization logic , based on the click stream input , is operable to categorize the canonical term into another category . US7146416B1 CLAIM 42 . A computer-aided method of accumulating counts for categories and subjects of search events , comprising ; receiving a search request (search request) from a client ; canonicalizing the search request into a canonical search term ; providing a set of search results in response to the search request ; accepting a selection from the client ; determining whether the search request should be canonicalized into at least one other canonical search term based on the selection ; incrementing counts associated with canonical search terms into which the search request was canonicalized ; associating each of the canonical search terms with at least one category ; and normalizing the counts associated with canonical search terms to obtain indicia of change in aggregate user interest in the canonical search terms . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | CN101140588A Filed: 2007-10-10 Issued: 2008-03-12 一种关联关系搜索结果的排序方法及装置 (Original Assignee) 华为技术有限公司 舒琦, 文坤梅, 孙小林, 赵艳涛 |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories (排序模块) , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords with search terms in a search request provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij (的集合) + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
CN101140588A CLAIM 3 . 根据权利要求1或2所述的方法，其特征在于，每个搜索结果信息的领域相关度DR通过如下公式计算： 其中，R为所述每个搜索结果信息对应的关联关系： R＝{O1，P1，O2，P2，O3， . . . . . . ，On-1，Pn-1，On}，其中n等于length(R)； length(R)为该关联关系的路径长度； d为调整因子，0＜d＜1； Yi为在所述每个搜索结果信息对应的关联关系中，属于用户感兴趣的领域D的实例Oi和属性Pi的集合 (N W ij) ： Yi＝{Oi or Pi|Oi∈R∩Pi∈R∩Oi∈D∩Pi∈D} Ni为在所述每个搜索结果信息对应的关联关系中，不属于用户感兴趣的领域D的实例Oi和属性Pi的集合： Ni＝{Oi or Pi|Oi∈R∩Pi∈R∩OiD∩PiD}。 CN101140588A CLAIM 11 . 一种关联关系搜索结果的排序装置，其特征在于，包括： 本体解析模块，用于解析本体的各个实例的三元组信息，根据各个实例的三元组信息构建实例关联关系图； 关联关系搜索模块，用于根据输入的所述本体中的任意两个实例，遍历实例关联关系图中所述两个实例间的所有关联关系的路径，生成两个实例间的所有关联关系的搜索结果信息； 关联关系排序模块 (ranking categories) ，用于根据所述搜索结果信息，计算领域相关度和/或关联关系长度和/或关联关系频度；根据领域相关度或关联关系长度或关联关系频度、或者根据领域相关度、关联关系长度、关联关系频度的任意组合来对所述搜索结果信息进行排序。 |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | CN101159730A Filed: 2007-09-19 Issued: 2008-04-09 多媒体联络中心处理信息的方法、系统及装置 (Original Assignee) 华为技术有限公司 伍志勇 |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords with search terms in a search request (搜索数据) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue (对应关系) Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
CN101159730A CLAIM 1、一种多媒体联络中心处理信息的方法，其特征是，该方法包括： 存储客户接触信息对应的业务信息，业务信息对应的业务规则信息； 根据存储的对应关系 (relationship Issue) 将获取的客户接触信息匹配为业务信息，将业务信息匹配为业务规则，将匹配好的业务规则编译生成业务规则执行脚本，根据业务规则执行脚本执行业务规则，得到业务规则的执行结果。 CN101159730A CLAIM 9、 一种多渠道信息处理服务器，其特征是，包括：业务信息匹配模块、业 务规则匹配模块、业务规则脚本生成模块和执行模块；所述业务信息匹配模块，用于接收多渠道接入平台发来的客户接触信 息，利用搜索索引从数据库中搜索数据 (search request) 库中存储的客户接触信息对应的业务 信息，将客户接触信息匹配为业务信息，并将匹配好的业务信息发送给业务 规则匹配模块；所述业务规则匹配模块，用于接收业务信息匹配模块发来的业务信息， 并利用搜索索引从数据库中搜索预置的业务规则模版进行匹配，并将业务信 息套入匹配出的业务规则模版，形成所述的业务规则；将业务规则同时发送 给业务规则执行脚本生成模块和数据库；所述业务规则脚本生成模块，用于根据业务规则匹配模块发来的匹配好 的业务规则生成业务规则执行脚本，并发送给业务规则执行模块；业务规则执行模块，用于对业务规则执行脚本生成模块发来的业务规则 执行脚本进行解析，解析出具体的执行步骤和方法，并依照所述步骤和方法 执行业务规则，得到业务规则执行结果。 |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20080059308A1 Filed: 2007-08-31 Issued: 2008-03-06 Methods and apparatus for using poll results to target and/or select advertisements (Original Assignee) BUZZDASH Inc (Current Assignee) Tribune Interactive Inc David Gerken |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories (collaborative filtering) , each category having at least one keyword , each category having a plurality of associated documents , a search engine (collaborative filtering) identifying relevant categories based upon a comparison of category keywords with search terms in a search request (selecting advertisements) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20080059308A1 CLAIM 5 . The method of claim 3 , wherein collaborative filtering (ranking categories, search engine) is used in at least one of said analyzing and selecting steps . US20080059308A1 CLAIM 10 . The method of claim 9 , wherein said polling result information is sold to advertisers for use by said advertisers in selecting advertisements (search request) to be displayed . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20080016101A1 Filed: 2007-07-11 Issued: 2008-01-17 Systems and methods for dynamically updating relevance of a selected item (Original Assignee) Shopping com (Current Assignee) eBay Inc ; Shopping com Adam Ginsburg, Oren Glickamn, Amir Ashkenazi |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords with search terms in a search request provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank (providing rank) ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij (n storage) + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20080016101A1 CLAIM 1 . A system for updating the order of display of a plurality of items , the items that were retrieved in response to a search query , the system comprising : a server comprising : a server storage device ; a server processor connected to the server storage device , the server storage device storing a server program for controlling the server processor ; and wherein the server is operative to communicate with each of a plurality of workstations , each of the workstations comprising : a workstation storage (N W ij) device ; a workstation processor connected to the workstation storage device , the workstation storage device storing a workstation program for controlling the workstation processor ; and the workstation processor operative with the workstation program to : display the plurality of items ; receive a selection of one of the plurality of items ; the server processor operative with the server program to update the order of display of the plurality of items in response to the selection , the updating comprising : adjusting a value of the selected item with respect to the search query ; adjusting a value of each of the plurality of items that are displayed in a higher position than the selected item with respect to the search query ; and the workstation processor further operative with the workstation program to display a list of the plurality of items in response to the search query , the order of the list being based on an adjusted value associated with each of the items . US20080016101A1 CLAIM 36 . The method of claim 35 further comprising providing rank ( Rank ) ing information to a query integrator in order to rank a second plurality of items that were retrieved in response to a second query , the ranking information being based on an updated weight of the plurality of items . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | EP1862922A1 Filed: 2007-05-31 Issued: 2007-12-05 System and method for searching web services and generating a search index (Original Assignee) SAP SE (Current Assignee) SAP SE Marko Degenkolb, Ralf Halbedel, Martin Zurmuehl |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine (Web service) identifying relevant categories based upon a comparison of category keywords with search terms in a search request (search results) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
EP1862922A1 CLAIM 1 A method of generating a search index (140 ; 620) for searching web services (648) , a Web service (search engine) s Description Language (WSDL) document (624) being stored for each of the web services (152 ; 648) and in addition to the WSDL documents further unstructured descriptive information (626) being stored for at least some of the web services , the method comprising : - reading the WSDL documents , - reading the descriptive information , - generating the search index (140 ; 620) using the WSDL documents and the descriptive information . EP1862922A1 CLAIM 21 The method of claim 20 , wherein the search results (search request) are provided to the client in a sorted fashion . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | CN101067807A Filed: 2007-05-24 Issued: 2007-11-07 文本语义的可视化表示与获取方法 (Original Assignee) 上海大学 骆祥峰, 方宁, 徐炜民 |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords (关键词对) with search terms in a search request provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij (的集合) + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
CN101067807A CLAIM 1 . 一种文本语义的可视化表示与获取方法，其特征在于将文本语义划分为三个层次：离散的关键词的集合 (N W ij) 构成的文本低层语义、文本段落构成的文本主题作为文本的中层语义和由文本主题之间相互链接而构成文本篇章的高层语义；通过提取关键词和基于关键词权重的矩阵运算生成文本主题的语义矩阵，再通过文本主题的链接形成文本篇章语义。 CN101067807A CLAIM 2 . 根据权利要求1所述的文本语义的可视化表示与获取方法，其特征在于操作步骤如下：(1)将文本语义划分为三个层次：离散的关键词的集合构成的文本低层语义、文本段落构成的文本主题作为文本的中层语义和由文本主题之间相互链接而构成文本篇章的高层语义；(2)计算一个文本段落中的关键词的状态值和关键词之间的权重；(3)用关键词之间的权重、关键词的状态值和基于矩阵相乘运算的推理规则，计算各个关键词对 (category keywords) 文本主题的权重，生成文本主题的语义矩阵；(4)用文本段落的标题或文本段落中具有单词数与关键词数之比最大的语句形成文本主题中的主题结点名称；(5)找出要链接的文本主题中共同的关键词，根据共同出现的关键词对各自文本主题的权重，计算各个文本主题之间的权重，链接各个文本主题为文本篇章，并用有向图可视化文本篇章；(6)枝剪各个文本主题中所独有的关键词。 |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | WO2007115254A2 Filed: 2007-04-02 Issued: 2007-10-11 System and method for searching disparate datastores via a remote device (Original Assignee) Visto Corporation Sean M. Quinlan, Robert Standen, Haniff Somani |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine (search engine) identifying relevant categories based upon a comparison of category keywords with search terms in a search request (search results) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
WO2007115254A2 CLAIM 1 . A system for searching application services from a remote device comprising : at least one remote device ; at least one application service ; a networked search concentrator for transmitting search queries and results between the remote device and the application service ; and a first software module resident on the search concentrator for translating the query from the remote device Into a native interface format of each application service and for formattiEg the search results (search request) from the application sendee to the native interface format of each remote device . WO2007115254A2 CLAIM 6 . The system of claim L wherein the application service is selected from the group consisting of a database , a search engine (search engine) , a website with a program application programming Interface , and data collection , management , and storage services . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20070288433A1 Filed: 2007-02-28 Issued: 2007-12-13 Determining relevancy and desirability of terms (Original Assignee) eBay Inc (Current Assignee) eBay Inc Raghav Gupta, Sichun Xu |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords (extracted keyword) with search terms in a search request (search results) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20070288433A1 CLAIM 5 . The system of claim 1 , further comprising : a second receiver to receive a search query ; an extractor to extract keywords from the search query ; an adder to add the extracted keyword (category keywords) s to existing keywords ; a re-calculator to re-calculate a percentage value relating to each keyword , the percentage value representing a percentage of search queries that each of the existing keywords has been used in a plurality of searches ; and a storage operatively to store the re-calculated percentage value into a keyword database . US20070288433A1 CLAIM 11 . The system of claim 1 , further comprising : a second receiver to receive a sort request of search results (search request) ; a fetcher to fetch a list of keywords associated with the search results from a database ; and an adder to add up desirability values associated with each keyword . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | WO2007106269A1 Filed: 2007-02-08 Issued: 2007-09-20 Mining web search user behavior to enhance web search relevance (Original Assignee) Microsoft Corporation Yevgeny E. Agichtein, Eric D. Brill, Susan T. Dumais, Robert J. Ragno |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine (search engine) identifying relevant categories based upon a comparison of category keywords with search terms in a search request (search results) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
WO2007106269A1 CLAIM 1 . A computer-implemented system comprising the following computer-executable components : ■a user behavior component(104 , 315 , 515 , 610) that facilitates automatic interpretation of collective behavior of users (101 , 103 , 105) to estimate user preferences of search results (search request) (350 , 550) and a search engine (search engine) (102 , 202 , 340 , 540) that incorporates the collective behavior for determination of relevance and ranking of returned search results (350 , 550) . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | CN101110074A Filed: 2007-01-30 Issued: 2008-01-23 基于文件系统缓存的数据加速查询方法 (Original Assignee) 浪潮乐金信息系统有限公司 张明 |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine (文件检索) identifying relevant categories based upon a comparison of category keywords with search terms in a search request provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue (对应关系) Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
CN101110074A CLAIM 1、基于文件系统缓存的数据加速查询方法，其特征在于，在系统接收用户查询请求之后，先转到查询分析器，查询分析器的主要作用是分析查询条件，规一化查询条件等，然后经过文件缓冲器，分析现有的结果数据文件中是否存在满足当前查询需求，没有则从数据库中进行查询，并将最终的结果文件返回给数据处理器，数据处理器按照最终的查询要求，对数据进行过滤、排序等处理，将结果文件返回上层应用系统，具体的执行步骤如下： 步骤(1)、分析查询提交的查询条件，将查询条件分为数据库运算处理和数据处理器处理的两大部分，数据库运算处理主要是对数据的提取和逻辑计算部分的查询条件，数据处理器处理主要包括对结果数据的过滤和排序等操作； 步骤(2)、规一化查询条件，将查询条件统一成标准的查询条件，避免某些查询描述上不同而实际上是相同情况，规一化查询包括： 1)集合判断合并，将小集合的条件转换成大集合，例如查询条件是查询山东的济南、青岛、潍坊等17个地市所有的数据，而这17个地市的属于山东省这个集合，与查询山东结果是一样的，系统会先将这个查询条件转换为查询山东这个集合的数据，子集和全集的关系需要预先定义，一般各个系统中都会存在表示对应关系 (relationship Issue) 的字典表，利用这个字典表就可以描绘出子集和全集的关系； 2)查询条件排序，将查询条件按照固定顺序进行排列，采用字符的先后顺序，例如查询济南、青岛、潍坊这样一个地区条件顺序的数据，与查询青岛、济南、潍坊这样一个地区条件顺序的数据，结果是一样的，系统能够进行统一的顺序排列，使其成一个相同的查询条件； 步骤(3)形成统一的查询条件之后，送入到文件缓冲器中，文件缓冲器先找到对应的查询实例，例如要查询的报表的历史数据登记列表，再根据查询条件再登记列表中检索满足当前条件的历史数据文件，该索引列表记录了该查询实例历史数据的查询条件，查询时间，用户，使用次数等信息； 检索列表命中率的高低直接影响到加速的效果，因此为了提高查询文件缓冲器检索数据文件的命中率，系统通过采用如下检索方法： 1)从全集数据中获取子集的数据，如果要查询若干个子集，而这若干个子集恰好属于另外一个全集的一部分，系统将返回该数据文件。例如：查询济南、青岛两个地区的数据，系统先查找是否有对应这两个地区的数据，如果没有再从全省的数据集文件中查找，系统能够利用全省的数据集进行处理； 2)部分子集查找，如果要查询若干个子集，而这若干个子集只有部分被检索到，那么系统会到步骤(5)，只生成没有的部分子集，例如：查询济南、青岛两个地区的数据，系统只找到济南一个地区的数据，同时也没有全省的数据，系统将查询条件转化为只查询青岛，到数据库中进行查询， 为了提高文件缓冲器检索的高效性，降低检索文件所消耗的时间，系统通过采用如下方法以减少检索量； 1)采用按照查询实例分目录存贮，降低了检索量，系统会自动的针对每一个查询实例，例如：针对每一个报表，形成一个文件缓冲目录，每一个目录都有一个索引列表，每次查询只去检索对应的索引列表； 2)超期历史数据删除，保证历史的数据文件不至于过多，占用大量的存贮空间，也会造成检索文件造成过大，增大检索的时间，同时过早的历史数据对于用户的查询来说，使用的频率极低，没有缓冲再次使用的意义，系统会将超过保存周期和使用频率低的文件删除，从而减少文件缓冲列表的大小； 3)查询结果文件聚合，系统为了保证检索的高效性，避免文件的过多，系统会将多个子集文件合并成一个全集文件，例如：将山东省17地区的各个子集文件合并成为一个全省的数据文件； 步骤(4)根据检索返回的结果，判断是否全部存在所要的数据文件，如果存在转到步骤8，否则转到步骤5； 步骤(5)将分析后的查询条件在数据库中查询，生成所需要的数据文件，并存放到对应的数据目录中； 步骤(6)将生成的数据文件，登记到文件缓冲器的文件检索 (search engine) 列表中； 步骤(7)返回需要的结果数据文件编号； 步骤(8)根据返回的文件编号，获取数据文件； 步骤(9)数据处理器对数据返回的数据文件进行处理，从结果文件中还原出需要的查询数据，并且将一些查询条件，本来需要在数据库的运算转移到数据处理器处理，提高对历史数据文件再使用率，从而增加缓冲器的命中率，增加命中率的方法还包括： 1)选取查询所需要的数据集合，从全集合中过滤出需要的子集数据，例如从全省数据集中，获取济南、青岛的数据，或者将多个子集数据合并，例如将济南、青岛两个子集的数据，合并成所需要的数据集； 2)选取查询所需要的显示列，例如：一个结果数据文件中包含10列数据，从中过滤出需要的6列数据； 3)按照查询的要求对结果数据排序； 步骤(10)按照固定的存贮结构，将最终的结果数据返回给上层应用，处理结束。 |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20070174257A1 Filed: 2007-01-12 Issued: 2007-07-26 Systems and methods for providing sorted search results (Original Assignee) ROXSE LLC (Current Assignee) ROXSE LLC Bruce Thomas Howard |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine (search engine) identifying relevant categories based upon a comparison of category keywords with search terms in a search request (search request) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips (audio file) related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20070174257A1 CLAIM 1 . A method comprising : receiving a search request (search request) based on at least one keyword ; obtaining search results based on the at least one keyword ; sorting the obtained search results into at least two result groups based on sorting criteria ; and outputting at least a portion of the at least two result groups to a display device such that the outputted portions of the at least two result groups are displayed differently from each other in a user interface . US20070174257A1 CLAIM 9 . The method of claim 8 , wherein the plurality of file-types comprises at least two of the following : a word processing file , a spreadsheet file , an audio file (video clips) , a video file , a multimedia file , an image file , or a web site . US20070174257A1 CLAIM 26 . A search engine (search engine) system comprising : means for receiving a search request based on at least one keyword ; means for obtaining search results based on the at least one keyword ; means for sorting the obtained search results into at least two result groups based on sorting criteria ; and means for outputting at least a portion of the at least two result groups to a display device such that the outputted portions of the at least two result groups are displayed differently from each other in a user interface . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20070156669A1 Filed: 2006-11-16 Issued: 2007-07-05 Extending keyword searching to syntactically and semantically annotated data (Original Assignee) Insightful Corp (Current Assignee) Fiver LLC Giovanni Marchisio, Navdeep Dhillon, Carsten Tusk, Krzysztof Koperski, Jisheng Liang, Thien Nguyen, Matthew Brown |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine (specific relationship, search engine) identifying relevant categories based upon a comparison of category keywords with search terms (result data) in a search request (search results) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20070156669A1 CLAIM 8 . The method of claim 1 , further comprising : for the one or more corresponding relationship searches that succeed , evaluating results of the corresponding relationship search that succeeds to determine a plurality of specific relationship (search engine) queries to serve as additional suggested searches ; and forwarding indications of the plurality of specific relationship queries as additional suggested search tips . US20070156669A1 CLAIM 10 . The method of claim 1 wherein a corresponding relationship search that succeeds is determined by whether search results (search request) are produced from the executing the corresponding relationship search against the corpus . US20070156669A1 CLAIM 42 . A computer-implemented method of exporting result data (search terms) from a relationship search performed against a corpus of documents , comprising : executing a relationship search on the corpus of documents according to a relationship query to generate a search result having one or more sentences that match the query ; providing a visual interface for indicating one or more columns for formatting data from the search result and , for each such column , indicating a respective value that corresponds to a component of a relationship query ; and automatically formatting and storing the search result according to the one or more columns and their associated values by retrieving one or more terms from each sentence of the search result and storing the retrieved terms according to the indicated columns and their respective values . US20070156669A1 CLAIM 47 . A relationship search facility for exporting result data from a relationship search performed against a corpus of documents , comprising : a search engine (search engine) that is configured to execute a relationship search on the corpus of documents according to a received relationship query to generate a search result having one or more sentences that match the received query ; a visual interface that is configured to , when executed , indicate one or more columns for formatting data from the search result and , for each such column , indicate a respective value that corresponds to a component of a relationship query ; and an export facility that is configured to , when executed , automatically format and store the search result according to the one or more columns and their associated values . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20080140616A1 Filed: 2006-09-21 Issued: 2008-06-12 Document processing (Original Assignee) Praxeon Inc (Current Assignee) Praxeon Inc Nicolas Encina, Kevin Gilpin, Dennis Underwood |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine (search engine) identifying relevant categories based upon a comparison of category keywords with search terms in a search request (search results) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20080140616A1 CLAIM 2 . The system of claim 1 wherein the search logic includes an indexer operative to index the document fingerprints , and a search engine (search engine) operative to search the index based on the query fingerprints . US20080140616A1 CLAIM 38 . The system of claim 37 wherein the search result output is further operative to present a result list responsive to the search engine and operative to present search results (search request) for the search query . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20070136236A1 Filed: 2006-09-12 Issued: 2007-06-14 Service Broker Realizing Structuring of Portlet Services (Original Assignee) International Business Machines Corp (Current Assignee) International Business Machines Corp Timo Kussmaul, Andreas Arning |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine (Web service) identifying relevant categories based upon a comparison of category keywords with search terms in a search request (search request) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20070136236A1 CLAIM 5 . The method of claim 1 , wherein the Web Service Consumer inquiry is a request and comprises description details of a Web Service preknown by the search request (search request) er . US20070136236A1 CLAIM 10 . A system including a computer readable medium , said computer readable medium having program code stored thereon for operating a Web Services search method in a networked environment , wherein said program code for operating said Web service (search engine) s search method is operable when a Service Broker is inquired by a Service Consumer for offering Web Services , and a Service Provider provides an inquired Web Service to the Service Consumer , said program code comprising : program code for retrieving data mining input data relating to description details of the inquired Web Services from respective Service descriptions of the inquired Web Services ; program code for performing a data mining function on said data mining input data , wherein a clustering is performed with a distance calculation function including said description details , and wherein the clustering yields a cluster model comprising a plurality of clusters and a mapping for each Web Service to one of said clusters , wherein Web Services having a similar semantic meaning are collected in a single cluster , yielding a data mining result ; wherein said program code for performing said data mining function adds cluster information comprised of said data mining result to a service model and for storing this cluster information in a database ; and program code for offering search response data based on said cluster model in response to Web Services search operations . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | CN101097573A Filed: 2006-06-28 Issued: 2008-01-02 一种自动问答系统及方法 (Original Assignee) 腾讯科技（深圳）有限公司 杨海松 |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords (一个关键词) with search terms in a search request provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue (对应关系) Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
CN101097573A CLAIM 1、一种自动问答系统，包括接口单元、分词单元、推理单元、语言知识库、推理知识库，其特征在于，还包括： 关键词归一化表，用于存储同义关键词的分组，并在每一组同义词中确定一个关键词 (category keywords) ，作为该组同义词的归一化词； 归一化单元，用于接收所述分词单元输出的对用户输入问句分词后产生的关键词序列，并根据所获得的关键词，查询所述关键词归一化表，获得该关键词序列的每一个关键词的归一化词，从而获得对应于所述用户输入问句的归一化词序列，并将该归一化词序列输出到所述推理单元； 所述推理单元根据该归一化词序列查询所述推理知识库，找到与该归一化词序列具有相同关键词序列的设定问句与所述用户输入问句匹配，并查询该设定问句对应的答句，将该答句作为系统应答通过所述接口单元输出。 CN101097573A CLAIM 2、 根据权利要求1所述的自动问答系统，其特征在于，还包括推理知识 库生成子系统，该子系统包括：设定问句分词单元，用于接收知识库管理员输入的设定问句，并根据所述 语言知识库存储的关键词信息对该问句进行分词，获得对应所述设定问句的关 键词序列；更新单元，用于接收所述设定问句的关键词序列，以及管理员输入的对所 述设定问句的答句，将两者的内容以及对应关系 (relationship Issue) 存储到所述推理知识库供所述 推理单元查询。 |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20060218111A1 Filed: 2006-04-21 Issued: 2006-09-28 Filtered search results (Original Assignee) Cohen Hunter C Hunter Cohen |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords with search terms in a search request (search results) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank (red display) ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20060218111A1 CLAIM 1 . A method for ordering search results (search request) comprising : accessing a database including data related to direct and indirect contacts between a selected individual and others ; searching the database to determine a search result set ; determining a proximity between the selected individual and each of the others related to the search result set ; and ordering the search result set in accordance with the determined proximities . US20060218111A1 CLAIM 5 . A method for generating social network weighted group preferences , experiences , traits and/or other characteristics of individuals as expressed by a group , comprising : a database of contact relationships ; evaluation of proximity between direct and/or indirect contacts ; linking of one or more individual preferences , experiences , traits and/or other characteristics of individuals to individual contacts ; and the ordered and/or filtered display ( Rank ) or other reporting of characteristics exhibited by the group giving weight to such things as the frequency of the appearance of the characteristic and reflecting the proximity of the linked contact to the user and/or other contacts . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | JP2007233874A Filed: 2006-03-02 Issued: 2007-09-13 投稿処理装置 (Original Assignee) Nomura Research Institute Ltd; 株式会社野村総合研究所 Tatsumi Mashita, 竜実 真下 |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords with search terms in a search request (の要求) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips (の質問) related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
JP2007233874A CLAIM 1 クライアント端末から受信した投稿データを他のクライアント端末に対して電子的に公開する装置であって、 クライアント端末から投稿データの閲覧要求がなされたときに、要求された投稿データを送信する投稿データ送信部と、 投稿データの内容に対する評価を示す内容評価データを、その投稿データについて閲覧要求をしたクライアント端末から受信する内容評価受信部と、 各種投稿データに対する内容評価データを集計して、クライアント端末のユーザごとの評価傾向を内容評価傾向データとして保持する内容評価傾向保持部と、 内容評価傾向データを参照して、ユーザ間における評価傾向の近さを内容評価類似値として指標化する内容評価類似値計算部と、 投稿データの閲覧要求がなされたとき、その要求 (search request) 元のユーザと近い評価傾向にあるユーザを内容評価類似値に基づいて選定する類似ユーザ選定部と、 閲覧要求された投稿データに対する前記選定されたユーザの内容評価データを参照して、その投稿データの表示方法を決定する表示方法決定部と、 前記閲覧要求された投稿データを送信するときに、前記表示方法を示す表示指定データを送信する表示指定部と、 を備えることを特徴とする投稿処理装置。 JP2007233874A CLAIM 7 クライアント端末のユーザに対して所定の質問 (video clips) データを送信する質問データ送信部と、 前記質問データに対する回答データをクライアント端末から受信する回答データ受信部と、 回答データを集計して、クライアント端末のユーザごとの回答傾向を回答傾向データとして保持する回答傾向保持部と、 回答傾向データを参照して、ユーザ間における回答傾向の近さを回答類似値として指標化する回答類似値計算部と、を更に備え、 前記類似ユーザ選定部は、投稿データの閲覧要求がなされたとき、その要求元のユーザと近い回答傾向にあるユーザを回答類似値に基づいて選定することを特徴とする請求項１から６のいずれかに記載の投稿処理装置。 |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20060129550A1 Filed: 2006-01-18 Issued: 2006-06-15 Associating documents with classifications and ranking documents based on classification weights (Original Assignee) Hongyuan Zha; Sean Suchter (Current Assignee) R2 Solutions LLC ; Altaba Inc Hongyuan Zha, Sean Suchter |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords with search terms in a search request provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N (intermediate values) NoS i + k 2 * ∑ i = 1 N W (intermediate values) ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j (said list) = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20060129550A1 CLAIM 17 . The method of claim 15 , wherein determining the diversity of domains in which there are other hosts that link to the particular host comprises : determining , for each domain , a relative domain frequency ; determining , for each domain , an intermediate value that is equal to the relative domain frequency of the domain divided by a summation of relative domain frequencies for all domains ; and determining an entropy value for the particular host as the summation of the products , for all domains , of the intermediate values (N W, N W ij, N ) for those domains and a logarithm of the intermediate values for those domains . US20060129550A1 CLAIM 18 . A method of presenting a ranked list of documents to a user , comprising : receiving search query terms from the user ; ranking a set of documents based on said search query terms and based on region information associated with a document ; and presenting , to said user , a list of documents that includes a first document whose rank was improved based on region information associated with said first document ; wherein said list (∑ j) includes a second document whose rank was not improved based on region information associated with said second document . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20060080303A1 Filed: 2005-10-07 Issued: 2006-04-13 Method, apparatus, and computer program product for indexing, synchronizing and searching digital data (Original Assignee) Computer Associates Think Inc (Current Assignee) Google LLC Antony Sargent, Erik Kay, David Moore, Daniel Willhite, Linus Upson |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories (outputting step) , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords (more search) with search terms (search terms) in a search request provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20060080303A1 CLAIM 25 . The method of claim 1 , wherein the searching and outputting step (ranking categories) s are performed during the indexing step . US20060080303A1 CLAIM 34 . The method of claim 1 , wherein the searching step comprises allowing for autocompletion of search terms (search terms) . US20060080303A1 CLAIM 37 . The system of claim 36 , wherein the graphical user interface includes one or more search (category keywords) areas in which the search commands are entered . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | JP2006202253A Filed: 2005-04-26 Issued: 2006-08-03 情報評価装置、コンテンツ検索装置、情報評価方法、コンテンツ検索方法、それらのプログラム及び記録媒体 (Original Assignee) Nippon Telegr & Teleph Corp <Ntt>; 日本電信電話株式会社 Takashi Fujimura, Takashi Inoue, Naoto Tanimoto, 孝史 井上, 考 藤村, 直人 谷本 |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine (検索方法, 検索手段) identifying relevant categories based upon a comparison of category keywords with search terms in a search request provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue (コンテンツサーバ装置, の関係, 関係式) Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
JP2006202253A CLAIM 2 請求項１に記載の情報評価装置であって、 前記スコア計算手段が、 さらに前記情報提供リンク情報又は前記情報評価リンク情報と前記固有ベクトルとを用い、これらと何れかの前記スコアとの定義された関係を示す関係式 (relationship Issue) に従い、何れかの前記スコアを算出し、当該スコアを情報評判スコア格納手段、情報提供スコア格納手段又は情報評価スコア格納手段に格納させる手段である、 ことを特徴とする情報評価装置。 JP2006202253A CLAIM 3 請求項１に記載の情報評価装置であって、 前記スコア計算手段が、 前記情報提供リンク格納手段に格納された前記情報提供リンク情報を検索し、前記利用者ＩＤと前記コンテンツＩＤとの組合せ毎に、当該組合せを有する前記情報提供リンク情報の個数を数え、当該個数を当該組合せに対応する行列成分の要素とした隣接行列（情報提供リンク隣接行列）を生成して出力する第１隣接行列生成手段と、 前記情報評価リンク格納手段に格納された前記情報評価リンク情報を検索し、前記利用者ＩＤと前記コンテンツＩＤとの組合せ毎に、当該組合せを有する前記情報評価リンク情報の前記評価情報の値を加算し、当該加算値を当該組合せに対応する行列成分の要素とした隣接行列（情報評価リンク隣接行列）を生成して出力する第２隣接行列生成手段と、 前記情報提供リンク隣接行列と前記情報評価リンク隣接行列とから、前記スコア推移行列（前記情報提供リンク隣接行列と前記情報評価リンク隣接行列と何れかの前記スコアとの関係 (relationship Issue) を示す行列）の固有ベクトルを算出し、この固有ベクトルの要素を何れかの前記スコアとして出力する固有ベクトル算出手段と、 前記スコアを、前記情報評判スコア格納手段、情報提供スコア格納手段又は情報評価スコア格納手段の何れかに格納させる書き込み手段と、 を備える手段である、 ことを特徴とする情報評価装置。 JP2006202253A CLAIM 7 コンテンツサーバ装置 (relationship Issue) に格納されたコンテンツに関する情報を提供するコンテンツ検索装置であって、 前記コンテンツが有する情報であるコンテンツ情報を受信するコンテンツ情報受信手段と、 前記コンテンツ情報を格納するコンテンツ情報格納手段と、 前記コンテンツ情報格納手段に格納された前記コンテンツ情報を用い、コンテンツを提供した利用者の利用者ＩＤと、前記利用者によって提供されたコンテンツの識別子であるコンテンツＩＤと、が関連付けられた情報提供リンク情報を生成して出力する情報提供リンク生成手段と、 前記コンテンツ情報格納手段に格納された前記コンテンツ情報を用い、コンテンツを評価した利用者の利用者ＩＤと、前記利用者によって評価されたコンテンツの識別子であるコンテンツＩＤと、前記コンテンツの評価者が前記コンテンツに対して行った評価の数値情報である評価情報と、が関連付けられた情報評価リンク情報を生成して出力する情報評価リンク生成手段と、 前記情報提供リンク情報を格納する情報提供リンク格納手段と、 前記情報評価リンク情報を格納する情報評価リンク格納手段と、 前記情報提供リンク情報と前記情報評価リンク情報とを用い、スコア推移行列（前記情報提供リンク情報と前記情報評価リンク情報と情報評判スコア又は情報提供スコアとの間の定義された関係を示す行列）の固有ベクトルを算出して、この固有ベクトルの要素を各コンテンツ情報に対応する前記情報評判スコア又は前記情報提供スコアとして出力する固有ベクトル算出手段と、 前記情報評判スコア又は前記情報提供スコアを、対応する前記コンテンツ情報に関連付けて、前記コンテンツ情報格納手段に格納させる書き込み手段と、 利用者端末装置から送信された検索条件を受信する検索条件受信手段と、 前記検索条件を充足する前記コンテンツ情報を、それらに関連付けられた前記情報評判スコア及び前記情報提供スコアの少なくとも一方とともに前記コンテンツ情報格納手段から抽出する検索手段 (search engine) と、を備える、 ことを特徴とするコンテンツ検索装置。 JP2006202253A CLAIM 14 コンテンツサーバ装置に格納されたコンテンツ関する情報を提供するコンテンツ検索方法 (search engine) であって、 コンテンツ情報受信手段において、前記コンテンツが有する情報であるコンテンツ情報を受信するステップと、 前記コンテンツ情報をコンテンツ情報格納手段に格納するステップと、 情報提供リンク生成手段において、前記コンテンツ情報格納手段に格納された前記コンテンツ情報を用い、コンテンツを提供した利用者の利用者ＩＤと、前記利用者によって提供されたコンテンツの識別子であるコンテンツＩＤと、が関連付けられた情報提供リンク情報を生成するステップと、 前記情報提供リンク情報を情報提供リンク格納手段に格納するステップと、 情報評価リンク生成手段において、前記コンテンツ情報格納手段に格納された前記コンテンツ情報を用い、コンテンツを評価した利用者の利用者ＩＤと、前記利用者によって評価されたコンテンツの識別子であるコンテンツＩＤと、前記コンテンツの評価者が前記コンテンツに対して行った評価の数値情報である評価情報と、が関連付けられた情報評価リンク情報を生成するステップと、 前記情報評価リンク情報を情報評価リンク格納手段に格納するステップと、 固有ベクトル算出手段において、前記情報提供リンク情報と前記情報評価リンク情報とを用い、スコア推移行列（前記情報提供リンク情報と前記情報評価リンク情報と情報評判スコア又は情報提供スコアとの間の定義された関係を示す行列）の固有ベクトルを算出して、この固有ベクトルの要素を各コンテンツ情報に対応する前記情報評判スコア又は前記情報提供スコアとして出力するステップと、 書き込み手段において、前記情報評判スコア又は前記情報提供スコアを、対応する前記コンテンツ情報に関連付けて、前記コンテンツ情報格納手段に格納させるステップと、 検索条件受信手段において、利用者端末装置から送信された検索条件を受信するステップと、 検索手段において、前記検索条件を充足する前記コンテンツ情報を、それらに関連付けられた前記情報評判スコア及び前記情報提供スコアの少なくとも一方とともに前記コンテンツ情報格納手段から抽出して出力するステップと、を備える、 ことを特徴とするコンテンツ検索方法。 |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20060161543A1 Filed: 2005-04-04 Issued: 2006-07-20 Systems and methods for providing search results based on linguistic analysis (Original Assignee) Tiny Engine Inc (Current Assignee) Tiny Engine Inc Xiao Feng, Sky Woo |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine (search engine) identifying relevant categories based upon a comparison of category keywords with search terms (search parameters) in a search request provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20060161543A1 CLAIM 1 . A method for providing search results based on linguistic analysis comprising : receiving content from one or more documents associated with search parameters (search terms) entered by a user ; analyzing language associated with the content based on linguistic parameters ; assigning a score to the content based on the analysis of the language ; and ordering the content by relevance to the user based on the assigned score . US20060161543A1 CLAIM 5 . The method as recited in claim 1 , further comprising forwarding the content to a commercial search engine (search engine) that presents the search results to the user based on the order of the content . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20060106788A1 Filed: 2005-03-29 Issued: 2006-05-18 Computer-implemented system and method for providing authoritative answers to a general information search (Original Assignee) Microsoft Corp (Current Assignee) Microsoft Technology Licensing LLC Brady Forrest |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine (search engine) identifying relevant categories based upon a comparison of category keywords with search terms in a search request (search results) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue (first member) Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j (said list) = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20060106788A1 CLAIM 7 . A computer-implemented , community-based question answering service comprising : a query input receiving component that receives a query from a first member (relationship Issue) of the service ; an answer receiving component that receives at least one answer from a second member of the service ; an incentive granting component that provides incentives to participants for answering questions ; an authority-assignment component that determines authority of at least one received answer ; a database of answered questions in communication with said authority-assignment component ; and an output component that provides authority-associated information to a search engine (search engine) . US20060106788A1 CLAIM 13 . A computer-implemented information search service comprising : a query input receiving component and a query result generation component , wherein said query result generation component comprises : a general information database producing a first output , said first output comprising search results (search request) from a general information-based search ; and a database of authoritative answers producing a second output , said second output comprising search results from a search of a community-based database of authoritative answers ; and a result combiner component which combines said first output and said second output to produce said query result . US20060106788A1 CLAIM 20 . The service of claim 19 , wherein said list (∑ j) integration subcomponent comprises an authority output subcomponent providing at least one field within said list indicating authority of at least one item in the result provided to said user interface . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20050256866A1 Filed: 2005-03-15 Issued: 2005-11-17 Search system and methods with integration of user annotations from a trust network (Original Assignee) Yahoo Inc (Current Assignee) Altaba Inc ; Slack Technologies Inc Qi Lu, Eckart Walther, David Ku, Chung-Man Tam, Kevin Lee, Zhichen Xu, Ali Diab, Kenneth Norton, Jianchang Mao |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords with search terms in a search request (search results) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue (report information) Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20050256866A1 CLAIM 25 . The method of claim 1 wherein generating the search report further includes : for each annotated hit , providing in the search report information (relationship Issue) extracted from at least one of the matching annotations . US20050256866A1 CLAIM 27 . The method of claim 1 further comprising : searching the store of annotations to identify one or more additional annotated hits , wherein each additional annotated hit corresponds to a document in the corpus for which the store of annotations includes an associated annotation for which the creating user is one of the trust network members and the associated annotation includes user-specific metadata that is determined to be relevant to the query ; and incorporating the additional annotated hits into the listing of the hits in the search results (search request) page . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | EP1557773A2 Filed: 2005-01-20 Issued: 2005-07-27 System and method for searching disparate resources (Original Assignee) Microsoft Corp (Current Assignee) Microsoft Corp Oliver Hurst-Hiller, Eddie L. Mays, Eric B. Watson |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords with search terms (search terms) in a search request (search request) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
EP1557773A2 CLAIM 3 The method of Claim 2 , wherein blending the disparate results includes ranking the results by the weight of the occurrence of the search term , displaying the ranked results by a category associated with the resource , and displaying the locations in which the search terms (search terms) occurred in comparable positions within each category . EP1557773A2 CLAIM 4 The method of Claim 1 , further comprising : capturing a context of the search request (search request) ; and wherein determining at least one relevant resource is based on the context of the search request . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | CN1716244A Filed: 2004-12-28 Issued: 2006-01-04 智能搜索、智能文件系统和自动智能助手的方法 (Original Assignee) 西安迪戈科技有限责任公司 梁平 |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords with search terms (包括搜索) in a search request provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue (相关关系) Rank ( X ) = k 1 * NoS x ∑ i = 1 N (式进行) NoS i + k 2 * ∑ i = 1 N W (式进行) ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
CN1716244A CLAIM 2 . 如权利要求1所述的智能搜索方法，其特征在于，进一步包括下列一项或多项：所说的一个或多个文件分类划分到的分类类别集包括一个分类层次结构；所述的对划入一个分类类别集的文件产生一个类别名；将符合用户提供的一个或多个搜索条件的一个或多个文件组织到一个甲分类类别集里是在一个用户操作的处理机上运行的；显示甲分类类别集里类别的类别名或链接，且对一个用户选择多于一个分类类别的响应包括显示所有所选的分类类别的交集里的文件的名字或链接；将符合用户提供的一个或多个搜索条件的一个或多个文件组织到一个甲分类类别集里对甲分类类别集里的类别用基于一个或多个排序准则的排序公式进行 (N W, N ) 排序；甲分类类别集有允许用户修改所说的排序准则或公式的用户接口；显示甲分类类别集里类别的类别名或链接，和排序最高的分类类别里的文件的名字或链接。 CN1716244A CLAIM 8 . 如权利要求7所述的智能搜索方法，其特征在于，进一步包括下列一项或多项：一个搜索元素包括下列一个或多个关键字：文件的特征、文件的分类类别，搜索的目的或对不同搜索结果的喜恶的描述；包括响应于一个用户用一个应用程序看、写、编辑、或处理一个文件时，指定此文件，并从此文件产生一个或多个搜索请求；进一步包括在下列一个或多个条件成立时，显示与所说的至少一个指定文件里提取的一个搜索元素相关的搜索结果：当接收到搜索程序送回的和所说的搜索元素相关的搜索结果；当此文件里的此搜索元素显示在一个应用程序的窗口里；当用户在此文件里选择此搜索元素；进一步包括把一或多个超链接和一个搜索元素或搜索元素的结合相结合，响应于一个用户使用一个输入器件选择一个此超链接，显示和此搜索元素或搜索元素的结合相关的搜索结果；进一步包括对搜索结果进行下列的一个或多个处理：过滤，分类，排序，提取搜索结果的摘要或总结；一个或多个搜索请求包括进行下列的一个或多个搜索：在一个或多个指定信息源里的文件里搜索，在一个最近文档的文件夹里的文件或链接的文件里搜索，在网络浏览器的历史纪录或喜好夹里所列的或相链接的文件里搜索；进一步包括产生重复的搜索请求；把所产生的请求在一段时间里按一个时间安排送交给一个搜索程序；从此搜索程序接收搜索结果；进一步包括探测以前一次搜索结果和后来一次搜索结果之间的改变，并在探测到改变时通知用户；探测以前一次搜索结果和后来一次搜索结果之间的改变进一步包括比较一个从以前一次搜索结果计算的数字摘要和一个从后来一次搜索结果计算的数字摘要；重复的搜索请求包括搜索 (search terms) 一组指定的信息源的搜索请求，并进一步包括探测在此一组指定的信息源里的信息的改变；进一步包括响应于用户使用一个输入器件指定一个文件，从用户如此指定的文件产生一个或多个搜索请求，在一个用户操作的处理机上运行一个搜索程序去搜索和此处理机相连通的一个或多个存储器里存储的文件来执行如此产生的搜索请求，并显示搜索程序基于如此产生的搜索请求找到的文件的名称或链接。 CN1716244A CLAIM 9 . 一个智能搜索的命题处理方法，其特征在于，包括从一个或多个信息体里提取一个甲论断或命题；将甲论断或命题普遍化扩展到含有一个或多个普遍化论断或命题的集合 (N W ij) ，此集合里的普遍化论断或命题和甲论断或命题且甲论断或命题是此集合的成员之一；基于此集合里的一个或多个普遍化论断或命题，处理此信息体里的文字信息。 CN1716244A CLAIM 10 . 如权利要求9所述的智能搜索的命题处理方法，其特征在于，进一步包括下列一项或多项：一个信息体包括下列中的一个或多项：在一个存储器里的一个文件，用户提供的输入，一个数据库，一个程序，一个或一组用户在一段时间里的行为的纪录，用户正在读、写或编辑的一个文件，用户最近读、写或编辑过的一个文件；将甲论断或命题普遍化包括将甲论断或命题中至少一部分用一个可以代表此部分的一个予以的描述来替换；处理此一个或多个信息体里的文字信息包括下列中的一个或多项：对此文字信息或此信息体进行分类或排序，决定一个普遍化论断或命题是否和另一个论断或命题有关系，将一个甲普遍化论断或命题送交到一个搜索程序以寻找一个或多个含有一个乙普遍化论断或命题的文件，此乙普遍化论断或命题和此甲普遍化论断或命题有相关关系 (relationship Issue) 。 |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20050108200A1 Filed: 2004-12-20 Issued: 2005-05-19 Category based, extensible and interactive system for document retrieval (Original Assignee) COGISUM INTERMEDIA AG (Current Assignee) COGISUM INTERMEDIA AG Frank Meik, Michael Wielsch |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine (search engine) identifying relevant categories based upon a comparison of category keywords with search terms (search terms, data space) in a search request (search results) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X (different categories) ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20050108200A1 CLAIM 20 . An interactive document retrieval system (100) in accordance with claim 1 , wherein : the query processor (400) is installed in at least one Web server connecting to the Internet or to an intranet ; the knowledge database (200) is installed on a database engine (1124) accessible to the Web server ; the requestor communicates with the Web server (1114 , 1116 , 1118 or 1120) using a computer (1102) having a browser (1104) also connecting to the Internet or to the same intranet ; and searches are performed by a search engine (search engine) (1128) accessible to the Web server (1114 , 1116 , 1118 or 1120) and conducting searches on the Internet or on the same intranet . US20050108200A1 CLAIM 51 . An interactive document retrieval system (100) in accordance with claim 1 , wherein the user is provided with a set of data space (search terms) s , each comprising a set of thematically connected documents . US20050108200A1 CLAIM 55 . An interactive document retrieval system (100) in accordance with claim 1 , wherein an universally applicable thesaurus with different categories (category X) and associated start documents is applied . US20050108200A1 CLAIM 57 . An interactive document retrieval system (100) in accordance with claim 1 , wherein search results (search request) are presented by means of a voice data output . US20050108200A1 CLAIM 73 . An interactive document retrieval system , comprising a knowledge database (1408) for relating identifications of analyzed documents to topics , a user interface (1402) for inputting a search query , a search engine (1406) for searching a resource for documents essentially matching an input search query and for outputting identifications of documents as a search result , a finding machine (1404) being supplied with the search result of the search engine (1406) , for accessing the knowledge database (1408) to check whether a document identified in the search result has already been analyzed before in relation with other search terms (search terms) than the present search term , forwarding the identification of a document along with its related topic as retrieved from the knowledge database (1408) to the user interface (1402) in case the document has already been analyzed before and its identification been stored together with its related topic in the knowledge database (1408) , and analyzing the identified document in case the document has not yet been analyzed before to relate a topic to the identification of the document and forwarding the identification of the document along with its related topic to the user interface (1402) . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20060080292A1 Filed: 2004-12-14 Issued: 2006-04-13 Enhanced interface utility for web-based searching (Original Assignee) DAR AL RIYADH HOLDING Co Ltd (Current Assignee) DAR AL RIYADH HOLDING Co Ltd Faisal Saud Alanzi |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine (search engine) identifying relevant categories based upon a comparison of category keywords with search terms (search terms) in a search request (search results) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i (different one) = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20060080292A1 CLAIM 6 . The method according to claim 1 , wherein displaying the text view of one of the web pages includes displaying a link for each of said one or more web pages in a first portion and displaying the text view of one of the web pages associated with one of the links of the one or more web pages in a second portion , wherein selecting a different link displays a different text version of a different one (∑ i) of the web pages associated with the different link in the second portion . US20060080292A1 CLAIM 34 . An interface utility for searching the world wide web , the interface utility comprising : (a) a text view component configured to display in a web page a text version of an individual search result returned by a search engine (search engine) ; and (b) a tabbed page component , the tabbed page component comprising at least one tabbed page configured to provide a plurality of search results (search request) returned by the search engine , wherein one of the plurality of search results includes the individual search result displayed by the text view component . US20060080292A1 CLAIM 35 . The interface utility according to claim 33 , further comprising a spell recommender component configured to return recommended search terms (search terms) based on search terms provided by a user before searching the world wide web . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20050120006A1 Filed: 2004-10-26 Issued: 2005-06-02 Systems and methods for enhancing web-based searching (Original Assignee) Geosign Corp (Current Assignee) TrueLocal Inc Timothy Nye |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories (more categories) , each category having at least one keyword , each category having a plurality of associated documents , a search engine (search engine) identifying relevant categories based upon a comparison of category keywords (more categories) with search terms in a search request (search request, search results) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20050120006A1 CLAIM 8 . An information gathering system for optimizing searching as in claim 7 wherein the search handler identifies the website content through a search engine (search engine) . US20050120006A1 CLAIM 25 . An information gathering system for optimizing searching as in claim 24 wherein the query includes attributes matching one or more categories (ranking categories, category keywords) in the updated classification scheme , where one or more entities is responsive to the query . US20050120006A1 CLAIM 53 . A method of optimizing searching in a data processing system comprising : storing data concerning entities , where each entity is stored according to a classification scheme that includes one or more predefined classifications ; storing website content for a plurality of the classified entities associated with at least one of the predefined classifications , where the website content is stored according to the classification scheme ; processing at least a portion of the website content to update the classification scheme ; searching for unclassified entities using at least a portion of the website content ; classifying the unclassified entities according to the classification scheme by identifying relationships between the unclassified entities and the classified entities ; and using the classification scheme , clustering search results (search request) . US20050120006A1 CLAIM 82 . A method of optimizing searching in a data processing system comprising : storing information about the entities that are included in a control group , where the control group includes categorized entities stored according to a classification scheme ; responding to a search request (search request) by processing search results responsive to the request ; and clustering the search results according to the classification scheme by comparing information about the control group with the search results . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US7386542B2 Filed: 2004-08-30 Issued: 2008-06-10 Personalized broadcast news navigator (Original Assignee) Mitre Corp (Current Assignee) OAKHAM TECHNOLOGIES LLC Mark T. Maybury, Warren R. Greiff, Stanley M. Boykin, Chadwick A McHenry, Lisa M Ferro |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords with search terms (search terms) in a search request provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips (video clip) related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US7386542B2 CLAIM 4 . The method of claim 1 , where step (f) comprises : providing a set of expanded search terms (search terms) to the user based on step (e) . US7386542B2 CLAIM 6 . The method of claim 1 , wherein step (b) comprises selecting at least one of video clip (video clips) , text transcript , skimmed results , streaming video access , video clip summary , person , organization , location , similar stories , and clip length . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20050076003A1 Filed: 2004-07-14 Issued: 2005-04-07 Method and apparatus for delivering personalized search results (Original Assignee) ADAPTIVE SEARCH LLC (Current Assignee) ADAPTIVE SEARCH LLC Paul DuBose, Gary Gagnon, Mark Glick |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine (search engine) identifying relevant categories based upon a comparison of category keywords with search terms (search terms) in a search request provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20050076003A1 CLAIM 1 . A method , comprising sorting results returned in response to a search query according to learned associations between one or more prior search query search terms (search terms) and selected results of said prior search queries . US20050076003A1 CLAIM 2 . The method of claim 1 , wherein the results returned in response to the search query are returned from a publicly accessible search engine (search engine) . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20050240580A1 Filed: 2004-07-13 Issued: 2005-10-27 Personalization of placed content ordering in search results (Original Assignee) Google LLC (Current Assignee) Google LLC Oren Zamir, Jeffrey Korn, Andrew Fikes, Stephen Lawrence |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine (search engine) identifying relevant categories based upon a comparison of category keywords with search terms in a search request (search results) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20050240580A1 CLAIM 9 . The method of claim 7 , wherein the user profile is based on information about the user , including information derived from a set of documents , the set of documents comprising a plurality of documents selected from the set consisting of documents identified by search results (search request) from a search engine (search engine) , documents linked to the documents identified by search results from the search engine , documents linked to the documents accessed by the user , and documents browsed by the user . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20050283468A1 Filed: 2004-06-22 Issued: 2005-12-22 Anticipated query generation and processing in a search engine (Original Assignee) Google LLC (Current Assignee) Google LLC Sepandar Kamvar, Taher Haveliwala, Glen Jeh |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords (more search) with search terms (search terms) in a search request provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20050283468A1 CLAIM 20 . The system of claim 18 , wherein the one or more characters of the portion are search terms (search terms) . US20050283468A1 CLAIM 71 . A method of processing a search request , comprising : receiving a portion of a search query ; extracting one or more search (category keywords) terms from the portion of the search query ; obtaining individual search results for each of the one or more search terms ; caching the individual search results ; combining the individual search results to produce final search results ; transmitting the final search results to a search requestor . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | WO2004111771A2 Filed: 2004-06-01 Issued: 2004-12-23 Serving advertisements using user request information and user information (Original Assignee) Google, Inc. Krishna Bharat, Stephen Lawrence, Mehran Sahami, Amit Singhal |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine (search engine) identifying relevant categories based upon a comparison of category keywords (demographic information) with search terms in a search request provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
WO2004111771A2 CLAIM 19 . The method of claim 1 wherein the information about the user includes demographic information (category keywords) . WO2004111771A2 CLAIM 24 . The method of claim 23 wherein the user behavior information includes at least one information item selected from a group of information items consisting of (A) information related to previous search queries submitted by the user , (B) information related to previous search queries submitted to a particular search engine (search engine) by the user , (C) information related to previous advertisements served for rendering to the user , (D) information related to previous advertisements served for rendering by the user and selected , (E) document information of a document viewed by the user , (F) document information about a document edited by the user , (G) previous purchases by the user , and (H) previous on-line purchases by the user . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20030217052A1 Filed: 2003-05-14 Issued: 2003-11-20 Search engine method and apparatus (Original Assignee) Celebros Ltd (Current Assignee) Celebros Ltd Tal Rubenczyk, Nachum Dershowitz, Yaacov Choueka, Michael Flor, Oren Hod, Assaf Roth |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords with search terms (search terms) in a search request provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue (following relationships, then c) Rank ( X ) = k 1 * NoS x ∑ i = 1 N (following relationships, then c) NoS i + k 2 * ∑ i = 1 N W (following relationships, then c) ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20030217052A1 CLAIM 137 . The method of claim 106 , wherein , if said analysis identifies an ambiguity , then c (N W, relationship Issue, N ) arrying out a stage of testing said query for semantic validity for each meaning within said ambiguity , and for each meaning found to be semantically valid , presenting said user with a prompt to resolve said validity . US20030217052A1 CLAIM 143 . The method of claim 142 , wherein said concept hierarchy comprises at least one of the following relationships (N W, relationship Issue, N ) (a) a hypernym-hyponym relationship , (b) a part-whole relationship , (c) an attribute value dimension—attribute value relation , (d) an inter-relationship between neighboring conceptual sub-hierarchies . US20030217052A1 CLAIM 206 . A query method for searching stored data items , the method comprising : receiving a query comprising at least two search terms (search terms) from a user , analyzing the query by determining a semantic relationship between the search terms thereby to distinguish between terms defining an item and terms defining an attribute value thereof , retrieving data items corresponding to at least one of identified items , using attribute values applied to said retrieved data items to formulate prompts for said user , asking said user at least one of said formulated prompts and receiving a response thereto using said received response to compare to values of said attributes to exclude ones of said retrieved items , thereby to provide to said user a subset of said retrieved data items as a query result . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20040220902A1 Filed: 2003-04-29 Issued: 2004-11-04 System and method for generating refinement categories for a set of search results (Original Assignee) International Business Machines Corp (Current Assignee) International Business Machines Corp Stephen Gates, Alexander Holt, Michael Moran, Pat Velderman |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories (ranking categories) , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords with search terms in a search request (search results) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i (steps i) = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20040220902A1 CLAIM 1 . A method for generating a set of categories in response to a search query , comprising : generating a set of search results (search request) in response to a query ; identifying at least one category from a hierarchy of categories for each search result ; rank-ordering each identified category based on a number of times the category was identified for the set of search results ; selecting an initial set of refinement categories based on the rank-ordering of the identified categories ; eliminating all categories from the initial set of refinement categories that meet an elimination criterion ; and displaying a resulting set of refinement categories . US20040220902A1 CLAIM 13 . The method of claim 1 , wherein the identifying steps i (∑ i, ix ∑ i) ncludes the step of using an automated categorization system to determine the category to which the document belongs . US20040220902A1 CLAIM 14 . A system for providing a set of refinement categories for a set of search results generated in response to a search query , comprising : a category identifier system that analyzes each search result and identifies at least one category from a hierarchy of categories for each search result , thereby providing a list of identified categories ; a ranking system that ranks each category in the list of identified categories ; and a selection system that selects a predetermined number of the highest ranking categories (ranking categories) from the list of identified categories to generate the set of refinement categories , wherein the selection system eliminates categories from the set of refinement categories if the category has a parent in the set of refinement categories . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US6963867B2 Filed: 2003-03-31 Issued: 2005-11-08 Search query processing to provide category-ranked presentation of search results (Original Assignee) A9 com Inc (Current Assignee) A9 com Inc James L. Ford, Christopher L. Scofield, Dwayne E. Bowman, Ruben E. Ortega |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine (time window) identifying relevant categories based upon a comparison of category keywords with search terms in a search request (search results) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X (particular items) ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US6963867B2 CLAIM 3 . The method of claim 2 , wherein the step of outputting identifiers of the multiple categories arranged in said order comprises generating a search results (search request) page in which each of the multiple categories is listed together with a selected subset of the responsive items falling within that category . US6963867B2 CLAIM 17 . A computer-implemented method of assisting users in locating items that are arranged by category within an electronic catalog , the method comprising : monitoring actions performed by a plurality of users , including user actions performed with respect to items in the electronic catalog , to generate user activity data ; calculating popularity scores for particular items (category X) in the catalog using said user activity date , said popularity scores being calculated automatically based primarily or exclusively on user activity data collected over a most recent time period , such that the popularity scores correspond to current preferences of users ; receiving a search query specified by a user , and identifying a set of items in the electronic catalog that are responsive to the search query (“responsive items”) , including items from multiple categories ; selecting an order in which to present the multiple categories to the user such that the order is dependent upon the popularity scores of responsive items , said order reflecting predicted levels of relevance of the categories to the search query ; and generating a search results display in which the multiple categories are presented in said order together with corresponding responsive items . US6963867B2 CLAIM 34 . The method of claim 26 , wherein the automated analysis of the user activity data is repeated over time using a sliding time window (search engine) such that the category scores , and associated category orderings , associated with a given search query change automatically over time to reflect current user preferences . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US6816850B2 Filed: 2003-03-20 Issued: 2004-11-09 Personalized search methods including combining index entries for catagories of personal data (Original Assignee) Ask Jeeves Inc (Current Assignee) IAC Search and Media Inc Gary A. Culliss |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories (more categories) , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords (more categories) with search terms (displaying results) in a search request provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US6816850B2 CLAIM 1 . A process of modifying an index that includes categories of personal data comprising : a) tracking user activity for articles contained in said index for query terms ; b) combining index entries for categories of personal data when said user activity is not significantly different for a said query term for two or more categories (ranking categories, category keywords) of personal data . US6816850B2 CLAIM 3 . A process of displaying results (search terms) in response to a query utilizing an index wherein articles are indexed based on query terms and personal data related to past users , wherein the index contains entries that have been combined based on similarity of past user activity with respect to results from searches , wherein the past users had different personal data associated with said users , but selected the same articles provided in response to similar query terms . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20030088553A1 Filed: 2002-11-23 Issued: 2003-05-08 Method for providing relevant search results based on an initial online search query (Original Assignee) Emergency 24 Inc (Current Assignee) Emergency 24 Inc Dante Monteverde |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords with search terms (search terms) in a search request (search results) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20030088553A1 CLAIM 1 . A method of determining relevant search results (search request) for an Internet based search query having at least one search term , the method comprising the steps of : providing a topical category database having a plurality of topical categories ; providing an Internet site database having Internet site information for at least one Internet site , each of the Internet sites having content ; assigning each of the Internet site informations in the Internet site database to at least one of the topical categories in the topical category database thereby creating assigned Internet sites ; providing a search term database having at least one search term , each of the search terms (search terms) having a definition ; assigning each of the search terms in the search term database to at least one of the topical categories in the topical category database thereby creating a search term assignment ; receiving at least one initial search term ; matching the initial search term with at least one of the search terms in the search term database thereby creating a matched search term ; associating the initial search term with the topical categories that the matched search term is assigned to thereby creating associated topical categories ; determining a most relevant associated topical category from the associated topical categories ; and retrieving the Internet site information for each of the assigned Internet sites assigned to the most relevant associated topical category . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US7043492B1 Filed: 2002-08-22 Issued: 2006-05-09 Automated classification of items using classification mappings (Original Assignee) Requisite Technology Inc (Current Assignee) International Business Machines Corp Michael Renn Neal, James Michael Wilmsen, Christopher Todd Black, d'Armond Lee Speers |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine (search engine) identifying relevant categories based upon a comparison of category keywords with search terms (higher hierarchical level) in a search request provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US7043492B1 CLAIM 6 . The method of claim 5 , wherein modifying comprises modifying the value to be at a higher hierarchical level (search terms) in the source classification system . US7043492B1 CLAIM 16 . A computer implemented apparatus comprising : a classification knowledge database containing a mapping of values from a source classification system to values in a destination classification system ; and a search engine (search engine) to select an attribute of the item associated with the source classification system , the search engine comparing the value of the attribute of the item to a set of possible values associated with the mapping , and selecting a destination classification for the item based on the comparison if the value of the attribute exists in the mapping , and the search engine modifying the value of the attribute , comparing the modified value to the set of possible values , and selecting a second destination classification for the item based on the comparison of the modified value if the modified value exists in the mapping , if the value of the attribute does not exist in the mapping . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US20020120609A1 Filed: 2001-10-22 Issued: 2002-08-29 Collaborative/adaptive search engine (Original Assignee) Lang Andrew K.; Kosak Donald M. (Current Assignee) I/P Engine Inc Andrew Lang, Donald Kosak |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine (search engine) identifying relevant categories based upon a comparison of category keywords with search terms in a search request (search results) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US20020120609A1 CLAIM 1 . A search engine (search engine) system comprising : a first system for receiving informons from a network on a continuing search basis , for filtering such informons for relevancy to a query from an individual user , and for storing a ranked list of relevant informons as a wire ; a second system for receiving informons from a network on a current demand search basis and for filtering such informons for relevancy to the query from the individual user ; and a third system for selecting at least one of the first and second systems to make a search for the query and to return the wire or demand search results (search request) to the individual user . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US6738764B2 Filed: 2001-05-08 Issued: 2004-05-18 Apparatus and method for adaptively ranking search results (Original Assignee) Verity Inc (Current Assignee) Valtrus Innovations Ltd Jianchang Mao, Mani Abrol, Rajat Mukherjee, Michel Tourn, Prabhakar Raghavan |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine (search engine) identifying relevant categories based upon a comparison of category keywords with search terms in a search request (search results) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US6738764B2 CLAIM 1 . A method of ranking search results (search request) , comprising : producing a relevance score for a document in view of a query ; calculating a similarity score for said query utilizing a feature vector that characterizes attributes and query words of a different query associated with said document ; and assigning a rank value for said document based upon said relevance score and said similarity score . US6738764B2 CLAIM 7 . A computer readable memory to rank search results , comprising : a search engine (search engine) to produce relevance search results based upon a query , said relevance search results including a list of documents , wherein each document includes an associated relevance score ; a viewed document database storing viewed document indicia corresponding to selected documents viewed in response to said relevance search results ; a viewed document processor to associate said viewed document indicia with different queries ; a vector constructor to form a feature vector for each viewed document , each feature vector characterizing attributes associated with a selected viewed document and query words of said different queries associated with said selected viewed document ; a similarity processor to calculate a similarity score for said query utilizing the feature vector of said selected viewed document ; and a ranking processor to assign a rank value for said selected viewed document based upon a function that incorporates the relevance score and said similarity score for said selected viewed document . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US6526440B1 Filed: 2001-01-30 Issued: 2003-02-25 Ranking search results by reranking the results based on local inter-connectivity (Original Assignee) Google LLC (Current Assignee) Google LLC Krishna Bharat |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords with search terms (search terms) in a search request provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i (∑ i) = 1 N (∑ i) NoS i + k 2 * ∑ i = 1 N W (∑ i) ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j (∑ i) = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US6526440B1 CLAIM 6 . The method of claim 3 , wherein the local score value is calculated for the particular one of the relevant documents as : ∑ i (N W, N W ij, N , ∑ i, ix ∑ i, ∑ j) = 1 k OldScore (BackSet (i)) m where OldScore(x) refers to the relevance score value for the particular document , BackSet refers to the sub-set of documents , the sum is taken over the first k documents in BackSet , where k is a predefined number , and m is a predetermined constant . US6526440B1 CLAIM 11 . A method of responding to a search query from a user , the method comprising : receiving the search query from the user ; generating a list of relevant documents based on search terms (search terms) of the query , each document in the list being associated with a relevance score corresponding to a relevance of the document ; calculating a local score for documents in the list of relevant documents , the local score quantifying an amount of inter-connectivity between documents in the list of relevant documents ; refining the relevance score based on the calculated local scores ; and returning a list of relevant documents to the user , the list being sorted based on the refined relevance scores . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US6658423B1 Filed: 2001-01-24 Issued: 2003-12-02 Detecting duplicate and near-duplicate files (Original Assignee) Google LLC (Current Assignee) Google LLC William Pugh, Monika H. Henzinger |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords with search terms in a search request (search results) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N (then c) NoS i + k 2 * ∑ i = 1 N W (then c) ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US6658423B1 CLAIM 2 . The method of claim 1 wherein the act of determining whether or not documents are near-duplicate documents includes : i) for any two documents , determining whether or not any fingerprints of a first of the two documents matches any fingerprints of a second of the two documents , and ii) if it is determined that a fingerprint of the first of the two documents does match a fingerprint of the second of the two documents , then c (N W, N ) oncluding that the two documents are near-duplicates . US6658423B1 CLAIM 14 . A method for filtering search results (search request) to remove near-duplicates , the method comprising : a) for each of a predetermined number of candidate search results , determining whether the candidate search result is a near-duplicate of another candidate search result ; and b) if it is determined that the candidate search result is a near-duplicate of another candidate search result , then rejecting the candidate search result wherein the act of determining whether a candidate search result is a near-duplicate of another candidate search result includes i) comparing a cluster identifier of the candidate search result with that of the other candidate search result , and ii) if the cluster identifiers of the two candidate search results match , then concluding that the two candidate search results are near-duplicates , and wherein cluster identifiers of the candidate search results are assigned by : i) determining whether or not a document corresponding to the candidate search result is a near-duplicate of any of previously processed documents , ii) if it is determined that the document corresponding to the candidate search result is not a near-duplicate of any previously processed document , then associating the document with a unique cluster identifier , and iii) if it is determined that the document corresponding to the candidate search result is a near-duplicate of a previously processed document , then associating the document corresponding to the candidate search result with a cluster identifier associated with the previously processed document . |
| US8849814B2 Filed: 2008-06-13 Issued: 2014-09-30 Searching, sorting, and displaying video clips and sound files by relevance (Original Assignee) NEWS DISTRIBUTION NETWORK Inc (Current Assignee) Relevant Holdings LLC Gregory Alton Peters, Paul Matthew Hernacki | US6539377B1 Filed: 2000-10-06 Issued: 2003-03-25 Personalized search methods (Original Assignee) Ask Jeeves Inc (Current Assignee) IAC Search and Media Inc Gary A. Culliss |
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| US8849814B2 CLAIM 1 . A computer-implemented method of ranking categories , each category having at least one keyword , each category having a plurality of associated documents , a search engine identifying relevant categories based upon a comparison of category keywords with search terms in a search request (search results) provided to the search engine , the computer-implemented method comprising : assigning a score to each category using the relationship Issue Rank ( X ) = k 1 * NoS x ∑ i = 1 N NoS i + k 2 * ∑ i = 1 N W ix ∑ i = 1 N ∑ j = 1 N W ij + k 3 * ∑ i = 1 N W ix * NoS i ∑ j = 1 N ∑ i = 1 N W ij * NoS i + k 4 * NoV x + k 5 * ∑ i = 1 N W ix * NoV i ∑ j = 1 N ∑ i = 1 N W ij * NoV i wherein : X denotes a category ; k1 is a coefficient representing a number of searches made regarding the category X (different categories) ; NoS x is the number of searches made regarding the category X ; N is a number of categories defined ; NoS i is a number of searches made for each category I ; k2 is a coefficient representing a weight of a relationship between the category X and all other categories ; W ix is a weighted relationship between the category X and another category I ; k3 is a coefficient representing a weighted number of searches made against related categories ; k4 is a coefficient representing a number of video clips related to the category X ; NoV x is the number of video clips related to the category X ; k5 is a coefficient representing a number of video clips related to categories related to the category X ; and , ranking the categories based upon the assigned scores , wherein the assigning of a score to each category and the ranking of the categories based upon the assigned scores are performed using software running on at least one computer including at least one non-transitory computer storage medium for storing the software for performing the assigning and the ranking . |
US6539377B1 CLAIM 1 . A process of presenting search results (search request) to a current user wherein the process of selecting the order of the squibs of articles presented in said search results comprises : a . matching personal data associated with said current user to personal data associated with said articles . US6539377B1 CLAIM 10 . A process of modifying an index that includes categories of personal data comprising : a . tracking user activity ; and b . combining index entries for categories of personal data when said user activity is not significantly different in response to search results presented to users for the same query term when said users have two or more different categories (category X) of personal data associated with them . |