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Science / Statistics / Semantics / SemEval / Random forest / Word-sense disambiguation / Statistical classification / Naive Bayes classifier / N-gram / Computational linguistics / Natural language processing / Linguistics


SEERLAB: A System for Extracting Keyphrases from Scholarly Documents Pucktada Treeratpituk1 Pradeep Teregowda2 Jian Huang1
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Document Date: 2010-12-02 17:54:26

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File Size: 138,29 KB

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City

Uppsala / /

Company

TF.IDF R C R C / /

Country

Sweden / /

Facility

University Park / Engineering Pennsylvania State University / University of California / /

IndustryTerm

baseline systems / /

MarketIndex

SET 100 / /

NaturalFeature

Random Forests / Random Forest / /

Organization

University of California / Berkeley / Pennsylvania State University / IDF / Association for Computational Linguistics / /

Person

Chao Chen / Treeratpituk / Thuy Dung Nguyen / Olena Medelyan / Matthew Wiener / Nam Kim / Lee Giles / Min-Yen Kan / Andy Liaw / Su Nam Kim / Leo Breiman / Timothy Baldwin / /

Position

extractor / candidate keyphrase extractor / /

ProvinceOrState

New Brunswick / California / /

PublishedMedium

Computational Linguistics / Machine Learning / /

Technology

Machine Learning / html / Random Forest algorithm / /

URL

http /

SocialTag