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Auto-detection of historical search context

  • US 8,972,397 B2
  • Filed: 03/11/2010
  • Issued: 03/03/2015
  • Est. Priority Date: 03/11/2010
  • Status: Active Grant
First Claim
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1. A volatile memory, non-volatile memory, optical disk, or hard drive storing computer-executable instructions which, when executed by a computer, cause the computer to perform acts comprising:

  • representing historical user behaviors of a user using a set of features, the set of features including click features and query features;

    training a classifier using training data comprising values for the features to identify a plurality of historical search contexts, wherein the plurality of historical search contexts include;

    a first historical search context having first values for the features, wherein the first values include;

    first click feature values for the click features, the first click feature values representing multiple first clicks entered by the user on multiple different first uniform resource locators (URLs) as part of the first historical search context, andfirst query feature values for the query features, the first query feature values representing multiple different first queries entered by the user as part of the first historical search context,a second historical search context having second values for the features, wherein the second values include;

    second click feature values for the click features, the second click feature values representing multiple second clicks entered by the user on multiple different second URLs as part of the second historical search context, andsecond query feature values for the query features, the second query feature values representing multiple different second queries entered by the user as part of the second historical search context;

    representing current user behavior during a current user session using third values for the features, wherein the third values include current click feature values for the click features and current query feature values for the query features, the current click feature values representing multiple current clicks entered by the user on multiple different current URLs during a current session and the current query feature values representing multiple different current queries entered by the user during the current session;

    during the current user session, determining that the current user behavior is relatively more similar to the first historical search context than the second historical search context, wherein the determining comprises;

    using the first click feature values, the second click feature values, and the current click feature values to analyze similarity of the multiple different current URLs clicked by the user during the current session to the multiple different first URLs clicked by the user as part of the first historical search context and the multiple different second URLs clicked by the user as part of the second historical search context, andusing the first query feature values, the second query feature values, and the current query feature values to analyze similarity of the multiple current queries entered by the user during the current session to the multiple different first queries entered by the user as part of the first historical search context and the multiple different second queries entered by the user as part of the second historical search context; and

    surfacing the first historical search context as part of the current session for the user.

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