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Learning to rank
Results: 420

#	Item
51	Tagging data as implicit feedback for learning-to-rank Beate Navarro Bullock Robert Jäschke Andreas Hotho Add to Reading List Source URL: www.websci11.org Language: English
52	Reciprocal Rank Fusion outperforms Condorcet and individual Rank Learning Methods G. V. Cormack C. L. A. Clarke Add to Reading List Source URL: plg.uwaterloo.ca Language: English - Date: 2009-05-19 18:21:37 French people Natural language processing Information retrieval Learning to rank Marquis de Condorcet Condorcet Age of Enlightenment
53	Reranking with Linguistic and Semantic Features for Arabic Optical Character Recognition Nadi Tomeh, Nizar Habash, Ryan Roth, Noura Farra Center for Computational Learning Systems, Columbia University {nadi,habash,ryanr, Add to Reading List Source URL: aclweb.org Language: English - Date: 2013-07-25 09:24:49 Computational linguistics Learning to rank Semantic similarity Optical character recognition Word error rate Word-sense disambiguation Statistical hypothesis testing Natural language processing Support vector machine Pattern recognition Language model Ranker
54	Folktale Classification using Learning to Rank Dong Nguyen, Dolf Trieschnigg, and Mari¨et Theune Human Media Interaction, University of Twente, Enschede, The Netherlands {d.nguyen,d.trieschnigg,m.theune}@utwente.nl} Ab Add to Reading List Source URL: www.dongnguyen.nl Language: English - Date: 2013-01-21 03:38:57
55	Learning to Rank for Robust Question Answering ∗ Arvind Agarwal Department of Computer Add to Reading List Source URL: www.prem-melville.com Language: English - Date: 2012-09-10 23:19:09
56	MultiText Legal Experiments at TREC 2007 Stefan Büttcher, Charles L. A. Clarke, Gordon V. Cormack, Thomas R. Lynam David R. Cheriton School of Computer Science University of Waterloo Waterloo, Ontario, Canada Add to Reading List Source URL: plg.uwaterloo.ca Language: English - Date: 2007-12-15 12:10:40 Information science Information retrieval Natural language processing Relevance feedback Okapi BM25 Ranking Document retrieval Search engine indexing Search engine N-gram Learning to rank
57	Efficient Learning of Mahalanobis Metrics for Ranking Daryl K. H. Lim DKLIM @ UCSD . EDU Department of Electrical and Computer Engineering, University of California, San Diego, CAUSA Gert Lanckriet Add to Reading List Source URL: acsweb.ucsd.edu Language: English - Date: 2014-06-16 18:55:07 Machine learning Learning Statistics Mathematics Learning to rank Support vector machine XQ Valuation Supervised learning Stochastic gradient descent
58	Microsoft Word - _paged_overlay_100.doc Add to Reading List Source URL: www.aviarampatzis.com Language: English - Date: 2013-10-16 04:53:55 Learning to rank Text Retrieval Conference XML-Retrieval Search engine indexing Document retrieval Tf*idf Character encodings in HTML Precision and recall Google Search Information science Information retrieval Science
59	Microsoft PowerPoint - [Lecture 3] Sparse and Low-Rank Representation with Applications to Visual Content Analysis.pptx Add to Reading List Source URL: www.acml2014.jvn.edu.vn Language: English - Date: 2014-11-06 20:46:32 Machine learning Sparse matrix Inpainting Regularization Mathematics Applied mathematics Basis pursuit denoising Image processing Statistics Image denoising
60	Paper Title (use style: paper title) Add to Reading List Source URL: www.aviarampatzis.com Language: English - Date: 2012-12-06 07:16:31 Text Retrieval Conference Search engine indexing XML-Retrieval Information extraction Precision and recall Relevance Tf*idf Query expansion Learning to rank Information science Information retrieval Science