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Model generation for ranking documents based on large data sets

  • US 7,743,050 B1
  • Filed: 04/18/2007
  • Issued: 06/22/2010
  • Est. Priority Date: 11/14/2003
  • Status: Expired due to Fees
First Claim
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1. A system, comprising:

  • a repository to store training data that includes a plurality of features; and

    one or more devices to;

    select a candidate condition that includes one or more of the features,estimate, after selection of the candidate condition, a weight for the candidate condition,form a new rule from the candidate condition and the weight,compare a likelihood of occurrence of the training data given a model with the new rule and a likelihood of occurrence of the training data given the model without the new rule,determine, based on the comparison, that a difference of the likelihood of occurrence of the training data in the repository given the model with the new rule and the likelihood of occurrence of the data in the repository given the model without the new rule is greater than a cost, andadd the new rule to the model upon determining that the difference of the likelihood of occurrence of the training data in the repository given the new rule and the likelihood of occurrence of the training data in the repository given the model without the new rule is greater than the cost.

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