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Generating search results based on user feedback

  • US 8,150,843 B2
  • Filed: 07/02/2009
  • Issued: 04/03/2012
  • Est. Priority Date: 07/02/2009
  • Status: Expired due to Fees
First Claim
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1. A computer-implemented method for processing search results, comprising:

  • receiving a search request against a corpus of documents, wherein the search request specifies one or more search terms;

    generating an initial set of search results, wherein the initial set of search results identifies a plurality of documents responsive to the search request, ranked in an initial ordering, and wherein each of the plurality of documents contains text;

    receiving user indication of;

    (i) at least one document relevant to the one or more search terms and (ii) at least one document irrelevant to the one or more search terms;

    by operation of one or more computer processors, training a new statistical classifier using each relevant document as a positive training example to form a first category of documents recognized by the statistical classifier and using each irrelevant document as a negative training example to form a second category of documents recognized by the statistical classifier, wherein the at least one relevant document and the at least one irrelevant document form a training set for the new statistical classifier;

    supplying each document in the initial set of search results and not in the training set, to the trained statistical classifier to obtain a measure of similarity between the respective document and at least one of the categories recognized by the trained statistical classifier;

    supplying one or more documents from the corpus and not included in the set of initial search results, to the trained statistical classifier to obtain a measure of similarity between each of the one or more documents and at least one of the categories recognized by the trained statistical classifier;

    re-ranking the initial set of search results based on the measures of similarity obtained from the trained statistical classifier, comprising ranking each document having a measure of similarity to the first category of documents that exceeds a first user-configurable threshold, ahead of each document having a measure of similarity to the second category of documents that exceeds a second user-configurable threshold; and

    outputting the re-ranked search results for display to a user.

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