Learning to rank

Results: 420



#Item
351Relevance / Precision and recall / Learning to rank / Language model / Ranking function / Document retrieval / Latent Dirichlet allocation / Search engine indexing / Probabilistic latent semantic analysis / Information science / Information retrieval / Science

2011 IEEE International Conference on Privacy, Security, Risk, and Trust, and IEEE International Conference on Social Computing Measuring Opinion Relevance in Latent Topic Space Wei Cheng∗ , Xiaochuan Ni† , Jian-Tao

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Source URL: www.cs.ucla.edu

Language: English - Date: 2012-02-28 09:51:37
352Information / Collaborative filtering / Recommender system / Learning to rank / Relevance / Precision and recall / Information science / Information retrieval / Science

GAPfm: Optimal Top-N Recommendations for Graded Relevance Domains ∗ Yue Shi Alexandros Karatzoglou

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Source URL: arxiv.org

Language: English - Date: 2013-07-15 22:36:01
353Learning to rank / Recommender system / Collaborative filtering / GroupLens Research / Precision and recall / Relevance / Ranking / Personalization / Information science / Information retrieval / Science

CLiMF: Collaborative Less-Is-More Filtering

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Source URL: ijcai.org

Language: English - Date: 2013-07-25 06:01:32
354Learning / Statistical classification / Neural networks / Information retrieval / Perceptron / Margin classifier / Learning to rank / Supervised learning / Recommender system / Statistics / Machine learning / Artificial intelligence

Online Structured Prediction via Coactive Learning Pannaga Shivaswamy Thorsten Joachims Department of Computer Science, Cornell University, Ithaca NY 14853

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Source URL: icml.cc

Language: English - Date: 2012-06-07 13:20:32
355Information / Recommender system / Learning to rank / Collaborative filtering / Information filtering system / GroupLens Research / Relevance / Precision and recall / Machine learning / Information science / Information retrieval / Science

xCLiMF: Optimizing Expected Reciprocal Rank for Data with Multiple Levels of Relevance Yue Shia , Alexandros Karatzogloub , Linas Baltrunasb , Martha Larsona , Alan Hanjalica a a

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Source URL: www.ci.tuwien.ac.at

Language: English - Date: 2013-07-09 16:51:43
356Information / Relevance feedback / Precision and recall / Ranking function / Relevance / Advantage / Learning to rank / IR evaluation / Information science / Information retrieval / Science

PDF Document

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Source URL: people.csail.mit.edu

Language: English - Date: 2006-06-11 22:54:12
357Internet search engines / Google / Human–computer interaction / Web search engine / Yahoo! / Enterprise search / Funnelback / European Conference on Information Retrieval / Learning to rank / Information science / Information retrieval / World Wide Web

DOC Document

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Source URL: irsg.bcs.org

Language: English - Date: 2014-01-30 12:06:05
358Relevance / Precision and recall / Tf*idf / Vector space model / Oracle Corporation / Relevance feedback / Learning to rank / Information science / Information retrieval / Science

Comparison of di erent Collection Fusion Models in Distributed Information Retrieval Alexander Steidinger Department of Computer Science Free University of Berlin Abstract

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Source URL: www.ercim.eu

Language: English - Date: 2008-12-08 05:11:33
359Birth certificate / Genealogy

PRE-K APPLICATION United Way of Santa Fe County Early Learning Center (located in the Aspen Community Magnet School Campus) Please rank the sessions you are interested in according to your preferences (1,2) Please leave

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Source URL: www.uwsfc.org

Language: English - Date: 2014-02-26 21:29:05
360Learning to rank / Relevance / Ranking function / IR evaluation / Discounted cumulative gain / Yandex / Web search engine / Search engine / Ranking / Information science / Information retrieval / Science

Quality-biased Ranking for Queries with Commercial Intent Alexander Shishkin Polina Zhinalieva [removed]

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Source URL: www.dl.kuis.kyoto-u.ac.jp

Language: English - Date: 2013-04-28 22:51:00
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