REAL TIME IMPLICIT USER MODELING FOR PERSONALIZED SEARCH
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Abstract
A method and apparatus for utilizing user behavior to immediately modify sets of search results so that the most relevant documents are moved to the top. In one embodiment of the invention, behavior data, which can come from virtually any activity, is used to infer the user'"'"'s intent. The updated inferred implicit user model is then exploited immediately by re-ranking the set of matched documents to best reflect the information need of the user. The system updates the user model and immediately re-ranks documents at every opportunity in order to constantly provide the most optimal results. In another embodiment, the system determines, based on the similarity of results sets, if the current query belongs in the same information session as one or more previous queries. If so, the current query is expanded with additional keywords in order to improve the targeting of the results.
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Citations
24 Claims
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1-23. -23. (canceled)
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24. A method for dynamically modifying search results comprising:
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receiving one or more keywords for use as search terms from a user; providing a set of search result objects on a first page of results displayed to said user; monitoring which of said objects is selected by said user; compiling information to infer user intent based on analyzing the content of an object the user clicks; and upon said user clicking to return from said object to said set of search result objects including said object, immediately automatically re-ranking said objects based on said user inferred intent, so that upon said user returning from said object to said set of search result objects including said object, without the user resubmitting the search, the re-ranked objects will be visible; wherein said re-ranking includes moving at least one object from a subsequent page, not originally visible to said user on said first page, onto said first page.
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Specification