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Natural language processing / Statistical theory / Computational linguistics / Relevance feedback / Text Retrieval Conference / Relevance / Precision and recall / Statistical inference / Maximum likelihood / Science / Information / Information retrieval


DUTH does Probabilities of Relevance at the Legal Track ∗ Dim P. Papadopoulos Vicky S. Kalogeiton Avi Arampatzis
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Document Date: 2011-03-01 11:30:28

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City

London / New York / /

Company

Cambridge University Press / Neural Networks / ACM Press / /

Country

United States / Greece / /

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Facility

Democritus University of Thrace / /

IndustryTerm

search engines / feedback algorithms / /

Organization

Cambridge University / Dim P. Papadopoulos Vicky S. Kalogeiton Avi Arampatzis Department of Electrical and Computer Engineering / idf / Democritus University / /

Person

R. Manmatha / Toni M. Rath / Jaap Kamps / Larry Wasserman / Brian D. Ripley / Fangfang Feng / Stephen Robertson / Christoph Bremkamp / Stephen Robertthe / Norbert Fuhr / Avi Arampatzis / Michael Pollmann / Vicky S. Kalogeiton Avi Arampatzis / Chris Buckley / Ulrich Pfeifer / N. L. Hjort / /

Position

representative / /

ProgrammingLanguage

XML / /

ProvinceOrState

New York / /

Technology

XML / feedback algorithms / avi / Newton-Raphson algorithm / /

URL

http /

SocialTag