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Ranking contextual signals for search personalization

  • US 8,706,725 B2
  • Filed: 03/14/2011
  • Issued: 04/22/2014
  • Est. Priority Date: 03/14/2011
  • Status: Active Grant
First Claim
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1. One or more computer-storage media devices storing computer-useable instructions that, when used by a computing device, cause the computing device to perform a method for using multiple contextual signals to re-rank search results, the method comprising:

  • receiving a set of non-contextual search results generated as a result of a search query entered by a user;

    receiving a set of contextual signals that include user-specific features that can be used to re-rank documents in the set of non-contextual search results, the set of contextual signals being received from a source other than the user;

    prior to communicating the set of non-contextual search results for presentation to the user, evaluating each of the user-specific features by a machine-learning model to establish an importance or relevance of each of the user-specific features in relation to the user and the search query;

    comparing the importance or relevance of the user-specific features, by the machine-learning model, with a current position of each document in the set of non-contextual search results, wherein the machine-learning model uses one or more algorithms to learn which of the user-specific features are more important in re-ranking the documents in the set of non-contextual search results;

    based on the comparison, algorithmically determining a new position of each document in the set of non-contextual search results; and

    utilizing the new position of each document in the list of search results to generate a set of contextual search results.

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