Learning ranking functions incorporating boosted ranking in...

Data processing: database and file management or data structures – Database and file access – Post processing of search results

Reexamination Certificate

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C707S723000

Reexamination Certificate

active

08051072

ABSTRACT:
Embodiments of the present invention provide for methods, systems and computer program products for learning ranking functions to determine the ranking of one or more content items that are responsive to a query. The present invention includes generating one or more training sets comprising one or more content item-query pairs, determining preference data for the one or more query-content item pairs of the one or more training sets and determining labeled data for the one or more query-content item pairs of the one or more training sets. A ranking function is determined based upon the preference data and the labeled data for the one or more content-item query pairs of the one or more training sets. The ranking function is then stored for application to query-content item pairs not contained in the one or more training sets.

REFERENCES:
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patent: 2009/0006360 (2009-01-01), Liao et al.
patent: 2009/0106221 (2009-04-01), Meyerzon et al.
patent: 2009/0132515 (2009-05-01), Lu et al.
patent: 2009/0222437 (2009-09-01), Niu et al.
Zha et al., “Incorporating Query Difference for Learning Retrieval Functions in World Wide Web Search”, Nov. 5, 2006, ACM, pp. 307-316.
Zheng et al., “A Regression Framework for Learning Ranking Functions Using Relative Relevance Judgments”, Jul. 23, 2007, ACM, pp. 287-294.
Zha, et al., “A General Boosting Method and Its Application to Learning Ranking Functions for Web Search”, 2007, NIPS, pp. 1-8.

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