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| First Page | Document Content | |
|---|---|---|
 Date: 2009-07-21 18:56:19Information retrieval Ensemble learning Learning to rank Ranking SVM Ranking function AdaBoost BM25 Support vector machine Boosting Machine learning Information science Artificial intelligence |
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SIGIR 2007 Proceedings Session 16: Learning to Rank II | Microsoft Word - LR4IR2009.v4-camera-nomark.docDocID: 1pnMD - View Document |
| Nonlinear Feature Selection with the Potential Support Vector Machine Sepp Hochreiter and Klaus Obermayer Technische Universit¨ at Berlin Fakult¨DocID: 1p8pc - View Document |
| Metric Learning to Rank Brian McFee Department of Computer Science and Engineering, University of California, San Diego, CAUSA Gert LanckrietDocID: 1oZVx - View Document |
| Perturbation based Large Margin Approach for Ranking Eunho Yang University of Texas at Austin Ambuj TewariDocID: 1m9Nw - View Document |
| Noname manuscript No. (will be inserted by the editor) Learning to Rank with (a Lot of ) Word Features Bing Bai · Jason Weston · David Grangier · Ronan Collobert · Kunihiko Sadamasa ·DocID: 19Cff - View Document |