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Learning to rank
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311	R Foundations and Trends in Information Retrieval Vol. 4, No[removed]–375 c 2010 M. Sanderson Add to Reading List Source URL: www.seg.rmit.edu.au Language: English - Date: 2013-02-26 19:52:06 Relevance IR evaluation Learning to rank Word-sense disambiguation Text Retrieval Conference Concept Search Information science Information retrieval Science
312	University of Lugano at TREC 2008 Blog Track Shima Gerani, Mostafa Keikha, Mark Carman, ∗ Robert Gwadera, Davide Taibi and Fabio Crestani University of Lugano Department of Informatics Add to Reading List Source URL: trec.nist.gov Language: English - Date: 2009-02-10 08:12:10 Information Text Retrieval Conference Learning to rank Relevance Precision and recall Ranking function Document retrieval Okapi BM25 Relevance feedback Information science Information retrieval Science
313	UniNE at TREC 2008: Fact and Opinion Retrieval in the Blogsphere Claire Fautsch, Jacques Savoy Computer Science Department, University of Neuchatel Rue Emile-Argand, 11, CH-2009 Neuchatel (Switzerland) {Claire.Fautsch, J Add to Reading List Source URL: trec.nist.gov Language: English - Date: 2009-02-10 08:12:16 Relevance feedback Precision and recall Document retrieval Relevance Subject Query expansion Search engine indexing Learning to rank XML-Retrieval Information science Information retrieval Science
314	Concept Maps: Theory, Methodology, Technology Proc. of the Second Int. Conference on Concept Mapping San José, Costa Rica, 2006 RANKING CONCEPT MAP RETRIEVAL IN THE CMAPTOOLS NETWORK Thomas C. Eskridge, Adrián Granados Add to Reading List Source URL: cmc.ihmc.us Language: English - Date: 2014-06-24 12:58:50 Tf*idf Web search engine Search engine indexing Web search query Precision and recall Query expansion Learning to rank Information science Information retrieval Vector space model
315	Accurately Interpreting Clickthrough Data as Implicit Feedback Thorsten Joachims Laura Granka Add to Reading List Source URL: www.cs.cornell.edu Language: English - Date: 2005-06-04 08:39:32 Relevance feedback Internet search engines World Wide Web Web analytics Relevance Learning to rank Google Search Google Search engine optimization Information science Information retrieval Human–computer interaction
316	NCBI at the 2013 BioASQ challenge task: Learning to rank for automatic MeSH indexing Yuqing Mao1, Zhiyong Lu1,* 1 National Center for Biotechnology Information (NCBI), 8600 Rockville Pike, Bethesda, MD Add to Reading List Source URL: bioasq.org Language: English - Date: 2014-07-11 11:09:45 Medical research Biological databases Bibliographic databases National Institutes of Health Search algorithms Medical Subject Headings PubMed MEDLINE Information retrieval Science Information science Library science
317	3: Data Tables[removed]Firm-level technology absorption* In your country, to what extent do businesses adopt new technology? [1 = not at all; 7 = adopt extensively] \| 2012–2013 weighted average RANK Add to Reading List Source URL: www3.weforum.org Language: English - Date: 2014-04-11 06:07:57 Index numbers 2000–01 National Basketball Association Eastern Conference playoff leaders Statistics Iris flower data set Machine learning
318	3: Data Tables[removed]Availability of latest technologies* In your country, to what extent are the latest technologies available? [1 = not available at all; 7 = widely available] \| 2012–2013 weighted average RANK Add to Reading List Source URL: www3.weforum.org Language: English - Date: 2014-04-11 06:07:52 Machine learning Economy of the Organisation of Islamic Cooperation Statistics Index numbers Iris flower data set
319	The Civic 50: Straight to the Point Summary: The Civic 50 is a national initiative to survey and rank S&P 500 corporations on how they engage with the communities they serve and institutionalize these practices in their Add to Reading List Source URL: www.pointsoflight.org Language: English - Date: 2013-10-21 13:53:09 Allstate Service-learning Core competency Knowledge Education Management Strategic management
320	Listwise Approach to Learning to Rank - Theory and Algorithm Fen Xia* Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, P. R. China. [removed] Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-05-21 03:01:42 Machine learning M-estimators Information retrieval Learning to rank Statistical theory Stochastic optimization Function Loss function Normal distribution Mathematics Statistics Mathematical analysis

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