Ranking items by optimizing ranking cost function

Details Ranking items by optimizing ranking cost function Ranking items by optimizing ranking cost function

2011-04-12

2011-04-12

Fleurantin, Jean B. (Department: 2162)

Data processing: database and file management or data structures

Database and file access

Post processing of search results

C707S728000, C707S730000

Reexamination Certificate

active

07925651

ABSTRACT:
A dependency structure is used to divide samples corresponding to items to be ranked into leaf nodes, based on the rank of the items. The dependency structure is trained by splitting or merging training data received at given nodes based on selected features and selected thresholds for those features. A metric is then calculated which is indicative of performance of the node, in splitting the data. The trained structure is then used during runtime to rank items.

REFERENCES:
patent: 6138115 (2000-10-01), Agrawal et al.
patent: 6795820 (2004-09-01), Barnett
patent: 6826576 (2004-11-01), Lulich et al.
patent: 2002/0123987 (2002-09-01), Cox
patent: 2004/0267770 (2004-12-01), Lee
patent: 2007/0033158 (2007-02-01), Gopalan
patent: 2007/0179966 (2007-08-01), Li et al.
patent: 2007/0192306 (2007-08-01), Papakonstantinou et al.
patent: 2007/0239702 (2007-10-01), Vassilvitskii et al.
patent: 2007/0255689 (2007-11-01), Sun et al.
patent: 2009/0319565 (2009-12-01), Greenwald et al.
Liang et al., “.Improve Decision Trees for Probability-Based Ranking by Lazy Learners”, IEEE, 2006, pp. 1-9. Download: http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=4031927&tag=1.
Provost et al., “Tree Induction for Probability-Based Ranking”, SpringerLink Contemporary, 2004, pp. 1-17. Download: http://www.springerlink.com/content/j25w11432k406231/fulltext.pdf.
PCT/US2008/050817 PCT Search Report and Written Opinion mailed Jun. 25, 2008.
Robert E. Schapire et al., “Improved Boosting Algorithms Using Confidence-rated Predictions”. pp. 1-40 (1998).
Jerome H. Friedman, “Greedy Function Approximation: A Gradient Boosting Machine”, Feb. 24, 1999. pp. 1-34.
Liew Mason et al., “Boosting Algorithms as Gradient Decent” pp. 512-518. (2000).
Yoav Freund et al., “An Efficient Boosting Algorithm for Combining Preferences”, 2003 pp. 933-969.

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