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Learning to rank
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#	Item
121	Introducing LETOR 4.0 Datasets Tao Qin and Tie-Yan Liu {taoqin,tyliu}@microsoft.com Microsoft Research Asia LETOR is a package of benchmark data sets for research on LEarning TO Rank, which Add to Reading List Source URL: arxiv.org Language: English - Date: 2013-06-11 20:03:19 Ranking Tf*idf Null Information science Information retrieval Learning to rank
122	UNIVERSITY OF CALIFORNIA, SAN DIEGO More like this: machine learning approaches to music similarity A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Add to Reading List Source URL: bmcfee.github.io Language: English - Date: 2015-03-31 11:15:28 Machine learning Science Multivariate statistics Natural language processing Statistical classification Learning to rank Support vector machine Dimension reduction Recall Statistics Information science Information retrieval
123	The Million Song Dataset Challenge Brian McFee∗ Thierry Bertin-Mahieux∗ CAL Lab Add to Reading List Source URL: bmcfee.github.io Language: English - Date: 2015-03-31 11:15:28 Recommender system Collaborative filtering Music information retrieval International Society for Music Information Retrieval Information filtering system Personalization Learning to rank Pandora Radio Netflix Information science Information retrieval Software
124	IEEE TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. 20, NO. 8, OCTOBERLearning Content Similarity for Music Recommendation Add to Reading List Source URL: bmcfee.github.io Language: English - Date: 2015-03-31 11:15:28 Learning to rank Vector quantization Collaborative filtering Music information retrieval Recommender system Similarity Information science Information retrieval Science
125	Proceedings of the 11th NTCIR Conference, December 9-12, 2014, Tokyo, Japan SEM13 at the NTCIR-11 IMINE Task: Subtopic Mining and Document Ranking Subtasks Md Zia Ullah Add to Reading List Source URL: research.nii.ac.jp Language: English - Date: 2014-11-26 23:45:56 Vector space model Web search query Search engine indexing MORE Information science Information retrieval Learning to rank
126	Improving Web Search Ranking by Incorporating User Behavior Information Eugene Agichtein Eric Brill Add to Reading List Source URL: www.mathcs.emory.edu Language: English - Date: 2006-08-29 13:39:12 Learning to rank Ranking function Web search query Recommender system IR evaluation Bing Discounted cumulative gain Web search engine Search engine Information science Information retrieval Relevance feedback
127	Early Exit Optimizations for Additive Machine Learned Ranking Systems B. Barla Cambazoglu Hugo Zaragoza Add to Reading List Source URL: www.wsdm-conference.org Language: English - Date: 2009-12-30 02:05:46 Learning to rank Tf*idf Precision and recall Search engine indexing Discounted cumulative gain Document retrieval PageRank Supervised learning Ranking SVM Information science Information retrieval Ranking function
128	THUSAM@NTCIR-IMine Cheng Luo, Xin Li, Alisher Khodzhaev, Fei Chen, Keyang Xu, Yujie Cao, Yiqun Liu, Min Zhang, Shaoping Ma Tsinghua University Dec 11th, 2014 Add to Reading List Source URL: research.nii.ac.jp Language: English - Date: 2015-01-05 21:56:54 Web search query Search engine Learning to rank Ranking Discounted cumulative gain Information retrieval Information Science
129	Proceedings Template - WORD Add to Reading List Source URL: www.wsdm-conference.org Language: English - Date: 2009-12-30 01:54:50 Inverted index Search engine indexing Tf*idf Document retrieval Relevance Learning to rank Information science Information retrieval Ranking function
130	A Model to Estimate Intrinsic Document Relevance from the Clickthrough Logs of a Web Search Engine Georges Dupret Ciya Liao Add to Reading List Source URL: www.wsdm-conference.org Language: English - Date: 2009-12-30 01:30:58 Discounted cumulative gain Web search query Ranking function Relevance Search engine Relevance feedback Web query classification Information science Information retrieval Learning to rank

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