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Linguistics / Statistical natural language processing / Computational linguistics / Bayesian statistics / Machine learning / Maximum-entropy Markov model / Hidden Markov model / Part-of-speech tagging / Word-sense disambiguation / Statistics / Markov models / Science


Conditional Structure versus Conditional Estimation in NLP Models Dan Klein and Christopher D. Manning Computer Science Department Stanford University Stanford, CA[removed] {klein, manning}@cs.stanford.edu
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Document Date: 2004-08-12 21:03:23


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City

San Mateo / Belmont / New York / Paris / /

Company

W. H. Press / PCL (flowers|1) PCL / estimation PCL / B. P. Flannery S. A. / C. Cambridge University Press / John Wiley & Sons / /

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Event

Product Issues / /

Facility

Carnegie Mellon University / University of Pennsylvania / /

IndustryTerm

natural language processing / /

MarketIndex

NNS / /

Organization

Cambridge University / University of Pennsylvania / Kenneth W. Church / Carnegie Mellon University / Stanford University Stanford / /

Person

Thorsten Brants / Claudia Leacock / Jerome H. Friedman / Scott M. Thede / A. Della Pietra / Mary P. Harper / Andrew Y. Ng / Mark Johnson / Adam L. Berger / J. Della Pietra / Alan Agresti / Kamal Nigam / Martin Chodorow / Fernando Pereira / William A. Gale / George A. Miller / Vincent J. Della / Andrew McCallum / Michael Jordan / Kristina Toutanova / Christopher D. Manning / Stephen A. Della / W. Church / Joshua Goodman / David Yarowsky / Morgan Kaufmann / /

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Position

conditional maximum entropy model / model / conditional shift-reduce parsing model / /

Product

RFEs / TnT / models / /

ProvinceOrState

New Brunswick / Pennsylvania / New York / California / Massachusetts / /

PublishedMedium

Computational Linguistics / /

Technology

natural language processing / Parsing algorithms / Data Mining / machine learning / /

URL

http /

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