Daniel C. Fain - Los Angeles CA, US Paul T. Ryan - Pasadena CA, US Peter Savich - Seattle WA, US
Assignee:
Overture Services, Inc. - Pasadena CA
International Classification:
G06F 17/00
US Classification:
707101, 707102, 707103 R, 715513, 715514
Abstract:
Described herein are methods for creating categorized documents, categorizing documents in a distributed database and categorizing Resulting Pages. Also described herein is an apparatus for searching a distributed database. The method for creating categorized documents generally comprises: initially assuming all documents are of type 1; filtering out all type 2 documents and placing them in a first category; filtering out all type 3 documents and placing them in a second category; and defining all remaining documents as type 4 documents and placing all type 4 documents in a third category. The apparatus for searching a distributed database generally comprises at least one memory device; a computing apparatus; an indexer; a transactional score generator; and a category assignor; a search server; and a user interface in communication with the search server.
System And Methods For Ranking The Relative Value Of Terms In A Multi-Term Search Query Using Deletion Prediction
Rosemary Jones - Pasadena CA, US Daniel C. Fain - Los Angeles CA, US
Assignee:
Yahoo! Inc. - Sunnyvale CA
International Classification:
G06F 17/30 G06F 7/00
US Classification:
707 3, 707 5, 707 6, 707 10, 7071041, 705 26
Abstract:
The likely relevance of each term of a search-engine query of two or more terms is determined by their deletion probability scores. If the deletion probability scores are significantly different, the deletion probability score can be used to return targeted ads related to the more relevant term or terms along with the search results. Deletion probability scores are determined by first gathering historical records of search queries of two or more terms in which a subsequent query was submitted by the same user after one or more of the terms had been deleted. The deletion probability score for a particular term of a search query is calculated as the ratio of the number of times that particular term was itself deleted prior to a subsequent search by the same user divided by the number of times there were subsequent search queries by the same user in which any term or terms including that given term was deleted by the same user prior to the subsequent search. Terms are not limited to individual alphabetic words.
Term Expansion Using Associative Matching Of Labeled Term Pairs
Jacob Sisk - Los Angeles CA, US Heidi Eldenburg Bramlet - Pasadena CA, US Daniel C. Fain - Los Angeles CA, US Jianchang Mao - San Jose CA, US Charity A. Rieck - Los Angeles CA, US
Assignee:
Yahoo! Inc. - Sunnyvale CA
International Classification:
G06F 17/00
US Classification:
706 45, 706 46, 706 47, 706 12, 707 3, 707 5
Abstract:
Various embodiments are directed to a system and method providing associative matching of terms. Candidate terms are selected for building one or more associative matching models from one or more selected candidate sources. Associativity is defined to give editors the ability to label sample associative term pairs from the one or more candidate sources. The editors label sample candidate term pairs as being related. Features are determined that can differentiate associative from non-associative pairs. The selected features are used to build a model. The model is applied to determine whether a received query-candidate pair are associative.
System And Methods For Indentifying The Potential Advertising Value Of Terms Found On Web Pages
Daniel C. Fain - Los Angeles CA, US Thomas Pierce - Pasadena CA, US
Assignee:
Yahoo! Inc. - Sunnyvale CA
International Classification:
G06F 17/30
US Classification:
707732, 707767, 705 1454, 705 1455
Abstract:
The present invention provides a method and system for identifying terms in a requested Web document which can be used to identify other web page documents in which the user is likely to have an interest. Terms on previously prepared lists are compared to the content of the Web page document, and where matches are found, mathematical techniques including linear regression can be used to determine the relevance of the textual term to the content of the page. This can be used to suggest other linked Web page documents in which the user is likely to have an interest. Where the prepared lists include a term that has been purchased by advertisers, and there is a match for that term on the Web page document, an ad which is likely to interest the reader can be displayed on the requested Web page document, and can include a link to the advertiser's web site.
Method And Apparatus For Categorizing And Presenting Documents Of A Distributed Database
Daniel C. Fain - Los Angeles CA, US Paul T. Ryan - Pasadena CA, US Peter Savich - Seattle WA, US
Assignee:
Overture Services, Inc. - Pasadena CA
International Classification:
G06F 17/30
US Classification:
707710, 707740
Abstract:
Described herein are methods for creating categorized documents, categorizing documents in a distributed database and categorizing Resulting Pages. Also described herein is an apparatus for searching a distributed database. The method for creating categorized documents generally comprises: initially assuming all documents are of type 1; filtering out all type 2 documents and placing them in a first category; filtering out all type 3 documents and placing them in a second category; and defining all remaining documents as type 4 documents and placing all type 4 documents in a third category. The apparatus for searching a distributed database generally comprises at least one memory device; a computing apparatus; an indexer; a transactional score generator; and a category assignor; a search server; and a user interface in communication with the search server.
Disambiguation Of Search Phrases Using Interpretation Clusters
John Joseph Carrasco - Pasadena CA, US Daniel Fain - Los Angeles CA, US Gary Flake - Altadena CA, US
International Classification:
G06F017/00
US Classification:
707003000
Abstract:
In one implementation a method for disambiguation of search phrases is provided, which may include identifying interpretation clusters using bidded search terms of content providers and influencing a position of a search result in a search results list based on the interpretation clusters. The search results list may be provided in response to a search query received by a searcher for review by the searcher. In one implementation a method is provided for interpretation clustering, which may include identifying terms and associated content providers and calculating a matrix from the identified terms and associated content providers. Similarity scores between content providers based on the matrix are calculated and interpretation clusters are assigned using the similarity scores. Bidded search terms and/or searcher clickthrough terms may be used. In one implementation, a method is provided for increasing the relevance of search results, which may include receiving a search query and identifying the search query as ambiguous. It may include clustering a plurality of search results for the search query into interpretation clusters and generating a search results list based on the interpretation clusters. The clustering of search results may include using bidded data, and/or using clickthrough data. In some implementations, search results from different interpretation clusters may be interleaved when generating the search results list.
Visually Emphasizing Query Results Based On Relevance Feedback
An example embodiment of the present invention provides processes for visually emphasizing the displayed URLs in query results based on implicit relevance feedback. In one process, the process identifies a web page which includes results returned by a search engine. Each result might include a displayed URL and an actual URL. The process determines whether the displayed URL matches any stored URLs which were included in previous results returned by the search engine and clicked through by the user. The process detects a click-through by matching the actual URL in an HTTP request emanating from a browser to an actual URL for a stored URL. The process visually emphasizes the displayed URL when presenting the web page to the user, if the displayed URL does not match any stored URL which has been clicked through and other factors indicate a probability the user will click through the displayed URL.
Spectrum Medical GroupHelen Devos Pediatric Neurology 35 Michigan St NE STE 3003, Grand Rapids, MI 49503 616 267-2500 (phone), 616 267-2501 (fax)
Education:
Medical School Indiana University School of Medicine Graduated: 1992
Languages:
English
Description:
Dr. Fain graduated from the Indiana University School of Medicine in 1992. He works in Grand Rapids, MI and specializes in Child Neurology. Dr. Fain is affiliated with Butterworth Hospital.
United States Air Force 2012 - 2015
Systems Engineer, Innovational Leader
The Aerospace Corporation 2012 - 2015
Systems Engineer
United States Air Force 2008 - 2014
Developmental Systems Engineer
United States Air Force 2008 - 2014
Program Manager
Education:
University of Connecticut
Bachelors, Electrical Engineering
Skills:
Systems Engineering Engineering Management Dod Top Secret Clearance Technical Leadership Program Management Dod Technology Integration Security Clearance Enterprise Architecture Vmware Software Acquisition Social Engineering Emotional Intelligence Critical Thinking Information Security Troubleshooting Root Cause Analysis Six Sigma Information Systems Problem Solving Requirements Management Systems Design C4Isr Requirements Analysis Integration Space Systems Process Improvement Engineering Life Cycle Planning Sustainable Architecture C4Isr Systems Sigint Imint Geoint Intelligence Systems Service Oriented Architecture Design Logistics Management Fmv Hbss Earned Value Management Roi Optimization Stakeholder Engagement Leadership Air Force