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Data management / Computing / Machine learning / Conditional random field / Theoretical computer science / Information extraction / Table cell / Table / Maximum-entropy Markov model / Markov models / Statistics / HTML


Table Extraction Using Conditional Random Fields David Pinto, Andrew McCallum, Xing Wei, W. Bruce Croft Center for Intelligent Information Retrieval University of Massachusetts Amherst 140 Governors Drive Amherst, MA 010
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Document Date: 2003-05-21 08:52:53

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File Size: 154,86 KB

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City

Crop / Toronto / Lima / Brussels / /

Company

CRFs / Intelligent Information Retrieval / Figure / /

Country

United States / Canada / /

Currency

USD / /

/

Event

Product Recall / Product Issues / /

Facility

University of Edinburgh / Intelligent Information Retrieval University of Massachusetts Amherst / /

IndustryTerm

Web documents / linear chain / earlier heuristic algorithm / data mining / language processing / /

MarketIndex

NONTABLE / /

Organization

Central Intelligence Agency / Intelligent Information Retrieval University of Massachusetts Amherst / National Science Foundation / W. Bruce Croft Center / University of Edinburgh / Center for Intelligent Information Retrieval / School of Cognitive Science / Association for Computational Linguistics / /

Person

M. King / R. Coleman / W. Li / Fangfang Feng / X. Wei / Aron Culotta / Andres Corrada-Emmanuel / Andrew McCallum / M. Branstein / Sha / Stephen Cronen-Townsend / Morgan Kaufmann / /

Position

author / heuristic table extractor / General / King / /

Product

presents / /

ProgrammingLanguage

Java / HTML / /

PublishedMedium

Computational Linguistics / /

Technology

speech recognition / Human Language Technology / Java / Viterbi algorithm / earlier heuristic algorithm / data mining / machine learning / HTML / /

URL

www.FedStats.gov / www.FedStats.com / http /

SocialTag