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Passage Retrieval by Shrinkage of Language Models Fei Song, Joe Vasak, and Wei Wang Dept. of Computing and Information Science University of Guelph Guelph, Ontario, Canada N1G 2W1 {fsong, jvasak, wwang01}@uoguelph.ca
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Company

MIT Press / Text-Based Intelligent Systems / Google / /

Country

Canada / /

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Facility

Information Science University of Guelph Guelph / /

IndustryTerm

statistical natural language processing / search terms / online documents / greedy algorithm / greedy curve-fitting algorithm / library catalogue search / Internet search engines / search results / retrieval systems / /

Organization

National Sciences and Engineering Council of Canada / MIT / University of Guelph / Computing and Information Science University of Guelph Guelph / IDF / American Society for Information Sciences / /

Person

Ricardo Baeza-Yates / Berthier Ribeiro-Neto / Chengxiang Zhai / Paul S. Jacob / Ronald Resonfeld / Andrew Y. Ng / John Lafferty / Tom Mitchell / Fei Song / Ntf / Stanley F. Chen / Andrew McCallum / Adwait Ratnaparkhi / Jay M. Ponte / Jeffrey C. Reynar / Bruce Croft / Christopher D. Manning / Joshua Goodman / Gerard Salton / Hinrich Schütze / Joe Vasak / Wei Wang / /

Position

general language model for information retrieval / Boolean model / inference network model / model information retrieval system / probabilistic model of information retrieval / suitable language model for passage retrieval / vector-space model / model for information retrieval / /

PublishedMedium

Machine Learning / /

Technology

Genomics / natural language processing / Knowledge Management / ASCII / 2006 Genomics Track Protocol / greedy algorithm / Machine Learning / greedy curve-fitting algorithm / /

URL

http /

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