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Learning to rank
Results: 420

#	Item
231	Earlybird: Real-Time Search at Twitter Michael Busch, Krishna Gade, Brian Larson, Patrick Lok, Samuel Luckenbill, and Jimmy Lin Twitter @michibusch @krishnagade @larsonite @plok @sam @lintool Abstract— The web today i Add to Reading List Source URL: www.umiacs.umd.edu Language: English - Date: 2012-01-25 09:54:55 Search engine indexing Learning to rank Inverted index Document retrieval Search engine Text Retrieval Conference Google Search Twitter Special Interest Group on Information Retrieval Information science Information retrieval Query expansion
232	Cache-Conscious Runtime Optimization for Ranking Ensembles Xun Tang, Xin Jin, Tao Yang Department of Computer Science, University of California Santa Barbara, CA 93106, USA Add to Reading List Source URL: www.cs.ucsb.edu Language: English - Date: 2014-06-02 10:18:37 Information CPU cache Central processing unit Computing Learning to rank Memory hierarchy Computer memory Cache Information science
233	Ready to Buy or Just Browsing? Detecting Web Searcher Goals from Interaction Data Qi Guo Eugene Agichtein Add to Reading List Source URL: www.mathcs.emory.edu Language: English - Date: 2010-06-13 20:16:05 Web query classification Search advertising Web search query Bing Learning to rank Information seeking behavior Google Search Yahoo! Search engine results page Information science Internet search engines Information retrieval
234	Beyond Position Bias: Examining Result Attractiveness as a Source of Presentation Bias in Clickthrough Data Yisong Yue∗ Rajan Patel Add to Reading List Source URL: www.yisongyue.com Language: English - Date: 2010-01-28 21:45:03 Click consonant Relevance feedback Google Search Relevance Web search engine Physical attractiveness Information science Information retrieval Learning to rank
235	Ready to Buy or Just Browsing? Detecting Web Searcher Goals from Interaction Data Qi Guo Eugene Agichtein Add to Reading List Source URL: www.mathcs.emory.edu Language: English - Date: 2010-06-13 20:16:05 Web query classification Search advertising Web search query Bing Learning to rank Information seeking behavior Google Search Yahoo! Search engine results page Information science Internet search engines Information retrieval
236	A Representation Theory for Ranking Functions Harsh Pareek, Pradeep Ravikumar Department of Computer Science University of Texas at Austin {harshp,pradeepr}@cs.utexas.edu Add to Reading List Source URL: papers.nips.cc Language: English - Date: 2015-01-20 12:41:39 Tensors Operator theory Multilinear algebra Differential geometry Hilbert space Learning to rank Self-adjoint operator Homogeneous polynomial Metric tensor Algebra Mathematics Mathematical analysis
237	Product Characteristic Weighting for Designer from Online Reviews: An Ordinal Classification Approach Jian Jin Ping Ji Add to Reading List Source URL: www.edbt.org Language: English - Date: 2012-02-05 21:26:08 Natural language processing Computational linguistics Machine learning Formal sciences Search engine indexing Algorithm Automatic summarization Sentiment analysis Learning to rank Information science Science Information retrieval
238	Classification-Enhanced Ranking Paul N. Bennett Krysta Svore Susan T. Dumais Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2010-02-11 03:40:21 Web search query Learning to rank Discounted cumulative gain Ranking function Web search engine Precision and recall Relevance feedback Ranking SVM Information science Information retrieval Web query classification
239	Perturbation based Large Margin Approach for Ranking Eunho Yang University of Texas at Austin Ambuj Tewari Add to Reading List Source URL: jmlr.csail.mit.edu Language: English - Date: 2012-04-26 08:57:12 Artificial intelligence Support vector machines Information retrieval Statistical classification Learning to rank Linear algebra Hinge loss Structured SVM Ranking SVM Mathematics Algebra Machine learning

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