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Inferring informational goals and preferred level of detail of answers based at least on device used for searching

  • US 7,430,505 B1
  • Filed: 01/31/2005
  • Issued: 09/30/2008
  • Est. Priority Date: 06/29/2001
  • Status: Expired due to Fees
First Claim
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1. A system for learning how to infer information goals from queries, comprising:

  • a natural language processor that produces a linguistic data concerning one or more linguistic features;

    a tagging tool that facilitates manipulating the linguistic data;

    one or more taggers that manipulate the linguistic data; and

    an inference model that stores information concerning conditional probabilities associated with the likelihood that one or more informational goals exist, where the conditional probabilities of the informational goals are determined, at least in part, from Bayesian statistical analysis performed on the linguistic data, wherein the inference model automatically selects a set of resources to search based upon an inferred age of a user and obtains information from extrinsic data associated with the query based at least in part on a type of device used.

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