Learning to rank

Results: 420



#Item
91PageRank / Latent semantic analysis / Learning to rank / Tf*idf / Probabilistic latent semantic analysis / Document retrieval / Relevance / Latent semantic indexing / Search engine indexing / Information science / Information retrieval / Vector space model

Effective Latent Space Graph-based Re-ranking Model with Global Consistency Hongbo Deng Dept. of CSE The Chinese University of

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Source URL: www.wsdm2009.org

Language: English - Date: 2009-04-14 09:42:13
92Web search query / Google Search / Discounted cumulative gain / Information science / Information retrieval / Learning to rank

On the Usefulness of Query Features for Learning to Rank Craig Macdonald Rodrygo L.T. Santos Iadh Ounis

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Source URL: dcs.gla.ac.uk

Language: English - Date: 2012-11-19 07:56:49
93Learning to rank / Query expansion / Text Retrieval Conference / Google Search / Document retrieval / Discounted cumulative gain / N-gram / Language model / Relevance feedback / Information science / Information retrieval / Science

The University of Amsterdam at the TREC 2011 Session Track Bouke Huurnink Richard Berendsen Edgar Meij

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Source URL: trec.nist.gov

Language: English - Date: 2012-02-03 09:41:34
94Text Retrieval Conference / Relevance feedback / Search engine indexing / Relevance / Document retrieval / Query expansion / Concept Search / Learning to rank / Information science / Information retrieval / Okapi BM25

TREC 2005 Genomics Track at I2R

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Source URL: trec.nist.gov

Language: English - Date: 2007-02-16 13:07:42
95Learning to rank / Web search query / Relevance / HTTP cookie / Web query classification / Information science / Information retrieval / Relevance feedback

Mining User Web Search Activity with Layered Bayesian Networks or How to Capture a Click in its Context Benjamin Piwowarski ∗

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Source URL: www.wsdm2009.org

Language: English - Date: 2009-04-14 09:42:00
96Learning to rank / Relevance feedback / Relevance / Crowdsourcing / Twitter / Information science / Information retrieval / Science

University of Glasgow at TREC 2011: Experiments with Terrier in Crowdsourcing, Microblog, and Web Tracks Richard McCreadie, Craig Macdonald, Rodrygo L. T. Santos and Iadh Ounis {richardm,craigm,rodrygo,ounis}@dcs.gla.ac.

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Source URL: dcs.gla.ac.uk

Language: English - Date: 2012-04-20 11:49:23
97Text Retrieval Conference / Relevance / Precision and recall / Document clustering / Cluster analysis / Search engine indexing / Relevance feedback / Learning to rank / Information science / Information retrieval / Science

National Taiwan University at Terabyte Track of TREC 2005

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Source URL: trec.nist.gov

Language: English - Date: 2006-02-21 09:28:40
98Learning to rank / Query expansion / Tf*idf / Relevance / Search engine indexing / Information science / Information retrieval / Twitter

TREC 2011 Microblog Track Experiments at Kobe University Taiki Miyanishi Naoto Okamura

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Source URL: trec.nist.gov

Language: English - Date: 2012-02-03 09:41:30
99BM25 / Query expansion / Relevance / Google Search / PageRank / Search engine optimization / Discounted cumulative gain / Search engine indexing / Bing / Information science / Information retrieval / Ranking function

Evaluating Learning-to-Rank Methods in the Web Track Adhoc Task. Leonid Boytsov and Anna Belova , TREC-20, November 2011, Gaithersburg, Maryland, USA

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Source URL: trec.nist.gov

Language: English - Date: 2012-02-03 09:41:36
100Learning to rank / Relevance feedback / Tf*idf / Google Search / Information science / Information retrieval / Twitter

ICTNET at Microblog Track TREC 2011† 1,2 1,2 1,2

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Source URL: trec.nist.gov

Language: English - Date: 2012-02-03 09:41:50
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