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Passage Scoring for Question answering via Bayesian inference on lexical relations Deepa Paranjpe, Ganesh Ramakrishnan, Sumana Srinivasan adeepa,hare @cse.iitb.ac.in, Dept. of Computer Science and En
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Document Date: 2004-02-13 07:01:57

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City

Dublin / Dempster / Cambridge / /

Company

MIT Press / BBN and associates / Walt Disney / ACM Press / Morgan Kaufmann Publishers Inc. / Learning Bayesian Networks / /

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Reorganization / /

Facility

Cornell University / Indian Institute of Technology / Stanford University / University of Pennsylvania / /

IndustryTerm

by-product / memory intensive algorithms / sentence processing / lexical network / passage-scoring algorithm / inference algorithm / belief network / search engines / Web Conference / generic algorithm / natural language processing techniques / Natural language processing / lexical networks / online memory / online lexical reference system / /

Organization

Royal Statistical Society / Vol. / Department of Computer Science / University of Pennsylvania / MIT / Stanford University / Indian Institute of Technology / Mumbai / Cornell University / /

Person

Rada Mihalcea / Mihai Surdeanu / Christiane Fellbaum / Roxana Girju / Paul Morarescu / Rebecca Bruce / Razvan Bunescu / Marius Pasca / Oren Etzioni / Mark Sanderson / Vasile Rus / Cody C. T. Kwok / Boris Katz / Gordon V. Cormack / Dan Moldovan / David D. Lewis / Thomas R. Lynam / Karen Sparck Jones / David Heckerman / Ellen Vorhees / L. A. Clarke / Deepa Paranjpe / /

Product

Expectation Maximization / WordNet / Falcon / /

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New Mexico / Pennsylvania / /

PublishedMedium

Machine Learning / Communications of the ACM / /

SportsLeague

Stanford University / /

Technology

natural language processing / passage-scoring algorithm / memory intensive algorithms / generic algorithm / inference algorithm / baseline QA algorithm / scoring algorithm / Expectation Maximization algorithm / Machine Learning / /

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