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Timestamp: 2015-08-04 17:03:33
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Matched Legal Cases: ['Application No. 200510085373', 'Application No. 200510085370', 'Application No. 200510085371', 'Application No. 200510085372', 'Application No. 2005203238', 'Application No. 2005203239', 'Application No. 2005203240', 'Application No. 2005203237', 'Application No. 06719537', 'Application No. 08799272', 'Application No. 08799272', 'Application No. 2', 'Application No. 2', 'Application No. 2', 'Application No. 2', 'Application No. 2', 'Application No. 200510085371', 'Application No. 200510085371', 'Application No. 200510085371', 'Application No. 200680007173', 'Application No. 05254644', 'Application No. 05254646', 'Application No. 05254647', 'Application No. 05254646', 'Application No. 2005', 'Application No. 2005', 'Application No. 20050068056', 'Application No. 2', 'Application No. 200510085371', 'Application No. 05254644', 'Application No. 05254647', 'Application No. 2005', 'Application No. 2005', 'Application No. 2005']

Patent US8078629 - Detecting spam documents in a phrase based information retrieval system - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign inAdvanced Patent SearchPatentsAn information retrieval system uses phrases to index, retrieve, organize and describe documents. Phrases are identified that predict the presence of other phrases in documents. Documents are the indexed according to their included phrases. A spam document is identified based on the number of related...http://www.google.com/patents/US8078629?utm_source=gb-gplus-sharePatent US8078629 - Detecting spam documents in a phrase based information retrieval systemAdvanced Patent SearchPublication numberUS8078629 B2Publication typeGrantApplication numberUS 12/578,339Publication dateDec 13, 2011Filing dateOct 13, 2009Priority dateJul 26, 2004Fee statusPaidAlso published asCA2513850A1, CA2513850C, CN1728142A, CN1728142B, DE602005026609D1, EP1622053A1, EP1622053B1, US7580921, US7603345, US20060018551, US20060294155, US20110131223Publication number12578339, 578339, US 8078629 B2, US 8078629B2, US-B2-8078629, US8078629 B2, US8078629B2InventorsAnna Lynn PattersonOriginal AssigneeGoogle Inc.Export CitationBiBTeX, EndNote, RefManPatent Citations (122), Non-Patent Citations (103), Referenced by (4), Classifications (11), Legal Events (2) External Links: USPTO, USPTO Assignment, EspacenetDetecting spam documents in a phrase based information retrieval system
This application is a continuation of U.S. patent application Ser. No. 11/478,330, filed Jun. 28, 2006, entitled “Detecting Spam Documents in a Phrase Based Information Retrieval System,” now U.S. Pat. No. 7,603,345, issued on Oct. 13, 2009, which in turn is related to U.S. patent application Ser. No. 10/900,021, filed Jul. 26, 2004, entitled “Phrase Identification in an Information Retrieval System,” now U.S. Pat. No. 7,580,921, issued on Aug. 25, 2009, each of which is incorporated by reference herein in its entirety.
FIG. 3 illustrates a portion of a document 300 during a traversal, showing the phrase window 302 starting at the word “stock” and extending 5 words to the right. The first word in the window 302 is candidate phrase i, and the each of the sequences i+1, i+2, i+3, 1+4, and i+5 is likewise a candidate phrase. Thus, in this example, the candidate phrases are: “stock”, “stock dogs”, “stock dogs for”, “stock dogs for the”, “stock dogs for the Basque”, and “stock dogs for the Basque shepherds”.
To summarize then, after this process there will be identified for each good phrase gj, a set of related phrases R, which are sorted in order of information gain I(gj, gk) from highest to lowest. In addition, for each good phrase there will be a cluster bit vector, the value of which is a cluster number identifying the primary cluster of which the phrase gj is a member, and the orthogonality values (1 or 0 for each bit position) indicating which of the related phrases in R are in common clusters with Thus in the above example, “Bill Clinton”, “President”, and “Monica Lewinsky” are in cluster 14 based on the values of the bits in the row for phrase “Bill Clinton”.
From the index 150 then, all of the (referencing document, referenced document) pairs are extracted for the anchor phrases Q. These pairs are then sorted by their associated (outbound score component, inbound score component) values. Depending on the implementation, either of these components can be the primary sort key, and the other can be the secondary sort key. The sorted results are then presented to the user. Sorting the documents on the outbound score component makes documents that have many related phrases to the query as anchor hits, rank most highly, thus representing these documents as “expert” documents. Sorting on the inbound document scores makes documents that are frequently referenced by the anchor terms the most highly ranked.
The search system 120 can use the date range information in several ways during the search and ranking operations. First, the search system 120 can use the date range as an explicit search delimiter. For example, a query may include terms or phrases and a date, such as “United States Patent and Trademark Office Dec. 4, 2004”. The search system 120 can identify the date term, and then select documents that have the desired phrase and which are indexed for a date range that includes the date term in the query. From the selected documents, the search system 120 can then obtain a relevance score for each document using the indexed relevance data associated with the date range. In this manner, an older or previous instance of a document may be retrieved instead of the current instance where it is more relevant to the search query. This is particularly useful for documents and pages that change frequently, such as the home pages of news sites and other sites containing frequently changing information.
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