Learning to rank

Results: 420



#Item
381Query expansion / Text Retrieval Conference / Document retrieval / Relevance feedback / Relevance / Precision and recall / Full text search / Learning to rank / XML-Retrieval / Information science / Information retrieval / Search engine indexing

Passage Retrieval Revisited

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Source URL: www.ir.iit.edu

Language: English - Date: 2011-02-22 14:46:52
382Discounted cumulative gain / Precision and recall / Ranking function / Relevance / Document retrieval / Mean reciprocal rank / IR evaluation / Learning to rank / Information science / Information retrieval / Science

[removed]Introduction to Information Retrieval

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Source URL: www.stanford.edu

Language: English - Date: 2014-03-27 16:28:57
383Decision trees / Ensemble learning / Computational statistics / Information retrieval / Learning to rank / Gradient boosting / Algorithm / Decision tree learning / Boosting / Machine learning / Artificial intelligence / Information science

LambdaSMARTTechReport.dvi

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Source URL: research.microsoft.com

Language: English - Date: 2008-10-16 19:13:52
384Ranking function / Discounted cumulative gain / Precision and recall / Relevance / Normal distribution / Search engine indexing / IR evaluation / Uncertain inference / Query likelihood model / Information science / Information retrieval / Learning to rank

BoltzRank: Learning to Maximize Expected Ranking Gain Maksims N. Volkovs

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Source URL: www.machinelearning.org

Language: English - Date: 2009-05-18 12:16:51
385Ranking function / Regression analysis / Ranking / Discounted cumulative gain / BM25 / Information retrieval / Learning to rank / Statistics / Econometrics / Statistical methods

The MachineLearnedRanking Story Jan Pedersen

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Source URL: jopedersen.com

Language: English - Date: 2009-06-30 12:07:57
386Ensemble learning / Natural language processing / Statistical classification / Learning / Gradient boosting / Supervised learning / AdaBoost / Learning to rank / Information retrieval / Statistics / Machine learning / Artificial intelligence

Multi-Task Learning for Boosting with Application to Web Search Ranking Olivier Chapelle

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Source URL: www.cse.wustl.edu

Language: English - Date: 2010-09-09 16:44:06
387Artificial intelligence / Science / Computational neuroscience / Computational statistics / Artificial neural network / Supervised learning / Learning to rank / Perceptron / Pattern recognition / Neural networks / Statistics / Machine learning

Learning to Rank using Gradient Descent Keywords: ranking, gradient descent, neural networks, probabilistic cost functions, internet search

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Source URL: research.microsoft.com

Language: English - Date: 2005-06-01 14:19:17
388Science / Machine learning / Support vector machines / Natural language processing / Statistical classification / Ranking SVM / Learning to rank / Supervised learning / Precision and recall / Statistics / Information science / Information retrieval

A Support Vector Method for Optimizing Average Precision Yisong Yue

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Source URL: www.cs.cornell.edu

Language: English - Date: 2007-11-29 16:03:23
389Machine learning / M-estimators / Information retrieval / Learning to rank / Statistical theory / Stochastic optimization / Function / Loss function / Normal distribution / Mathematics / Statistics / Mathematical analysis

Listwise Approach to Learning to Rank - Theory and Algorithm Fen Xia*

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Source URL: research.microsoft.com

Language: English - Date: 2009-08-07 05:09:10
390Standards-based education / Education reform / Outcome-based education / Pedagogy / Curriculum / E-learning / Tertiary Entrance Rank / GCE Advanced Level / New courses of study / Education / Education in Western Australia / Philosophy of education

A report to the Curriculum Council of Western Australia regarding assessment for tertiary selection

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Source URL: www.curriculum.wa.edu.au

Language: English
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