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Learning to rank
Results: 420

#	Item
291	How Fresh Do You Want Your Search Results? Shiwen Cheng, Anastasios Arvanitis, Vagelis Hristidis Department of Computer Science & Engineering University of California, Riverside, California, USA {schen064, tasos, vageli Add to Reading List Source URL: www.cs.ucr.edu Language: English - Date: 2013-07-30 00:18:35 Learning to rank Web query classification Web search query Okapi BM25 Discounted cumulative gain Relevance Google Search Search engine indexing Document retrieval Information science Information retrieval Ranking function
292	Learning to Rank Social Update Streams ∗ Liangjie Hong † , Ron Bekkerman§ , Joseph Adler§ , Brian Davison† † Dept. of Computer Science and Engineering, Lehigh University, Bethlehem, PA, USA § LinkedIn Corp., M Add to Reading List Source URL: www.hongliangjie.com Language: English - Date: 2012-06-06 15:54:53 Social information processing Information retrieval Collaboration Recommender system Machine learning Web 2.0 Collaborative filtering Social networking service Cold start Information science Statistics Collective intelligence
293	ICTNET at Session Track TREC 2013 , , , Add to Reading List Source URL: trec.nist.gov Language: English - Date: 2014-02-28 12:39:26 Natural language processing Computational linguistics Freebase Internet search engines Learning to rank Google Search N-gram Relevance Indri people Information science Science Information retrieval
294	Northeastern University Runs at the TREC13 Crowdsourcing Track Maryam Bashir, Jesse Anderton, Virgil Pavlu, Javed A. Aslam College of Computer and Information Science Northeastern University, Boston, USA {maryam,jesse,vi Add to Reading List Source URL: trec.nist.gov Language: English - Date: 2014-02-28 12:39:27 Information Learning to rank Relevance Precision and recall Crowdsourcing Quicksort Relevance feedback Text Retrieval Conference Information science Information retrieval Science
295	Overview of the TREC 2013 Federated Web Search Track Thomas Demeester1 , Dolf Trieschnigg2 , Dong Nguyen2 , Djoerd Hiemstra2 1 2 Add to Reading List Source URL: trec.nist.gov Language: English - Date: 2014-02-28 12:39:25 Learning to rank Query expansion Search engine indexing Search engine Web search engine Google Search Bing Precision and recall IR evaluation Information science Information retrieval Text Retrieval Conference
296	BIT and MSRA at TREC KBA CCR Track 2013 ∗ Jingang Wang Add to Reading List Source URL: trec.nist.gov Language: English - Date: 2014-02-28 12:39:25 Information retrieval Computational linguistics Machine learning Text Retrieval Conference Search engine indexing Information extraction Learning to rank Information science Science Natural language processing
297	PITT at TREC 2013 Contextual Suggestion Track Ming Jiang, Daqing He School of Information Sciences University of Pittsburgh {mij32, dah44}@pitt.edu Add to Reading List Source URL: trec.nist.gov Language: English - Date: 2014-02-28 12:39:27 Science Review websites Machine learning User interface techniques Recommender system Yelp Inc. Social networking service Learning to rank Bing Information science Information retrieval Information
298	ICTNET at Federated Web Search Track 2013 Feng Guan1,2,Yuanhai Xue1,2, Xiaoming Yu1, Yue Liu1, Xueqi Cheng1 1. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, [removed]University of Chinese Acad Add to Reading List Source URL: trec.nist.gov Language: English - Date: 2014-02-28 12:39:26 Google Search Federated search Web search engine Video search engine Okapi BM25 Learning to rank Information science Information retrieval Search engine
299	PKUICST at TREC 2013 Microblog Track ∗ Runwei Qiang Yue Fei Yihong Hong Jianwu Yang {qiangrw, feiyue, hongyihong, yangjw}@pku.edu.cn Institute of Computer Science and Technology Add to Reading List Source URL: trec.nist.gov Language: English - Date: 2014-02-28 12:39:27 Vector space model Learning to rank Tf*idf Relevance Query expansion Twitter Language model Ranking function Search engine indexing Information science Information retrieval Okapi BM25
300	University of Glasgow at TREC 2013: Experiments with Terrier in Contextual Suggestion, Temporal Summarisation and Web Tracks ∗ B. Taner Dinçer Add to Reading List Source URL: trec.nist.gov Language: English - Date: 2014-02-28 12:39:27 Learning to rank Relevance feedback Relevance Information retrieval Science Information

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