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System and method for personalized search, information filtering, and for generating recommendations utilizing statistical latent class models

  • US 7,328,216 B2
  • Filed: 08/11/2003
  • Issued: 02/05/2008
  • Est. Priority Date: 07/26/2000
  • Status: Expired due to Term
First Claim
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1. A method in a computer system for generating a recommendation list of desired items from a set of data including at least one of:

  • items, content descriptors for the items, user profiles about transactions, prior searches, user ratings and user actions, to generate a recommendation list of desired items, comprising the steps of;

    statistically analyzing the set of data to learn semantic associations between words within specific items of the set of data, storing the learned semantic associations in computer hardware;

    computing probabilities of each learned semantic association;

    receiving into the computer system for generating a recommendation list;

    an actual user profile, a user query; and

    a request to generate at least one recommendation list, items in the recommendation list being ranked by their likelihood of being the desired items;

    computing a probability of relevance of each item in the set of data to the actual user profile and said user query, the step of computing a probability of relevance including combining the learned semantic associations and the actual user profile; and

    generating at least one recommendation list of desired items.

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