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Using Association Rules between Terms and Nominal Syntagms for Tweet Contextualization Meriem Amina Zingla 1 University of Carthage, INSAT, LISI research Laboratory, Tunis, Tunisia [removed]
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Document Date: 2015-03-17 05:46:53

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File Size: 171,78 KB

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City

Washington / D.C. / Rome / Tunis / Sheffield / Gaithersburg / Valencia / Toulouse / /

Company

Twitter / CLEF 2012 Evaluation Labs / /

Country

France / Italy / Tunisia / United Kingdom / Spain / /

/

Facility

University of Stuttgart / University of Tunis El Manar / University of Carthage / /

IndustryTerm

web interface / greedy optimization algorithm / inner product / web links / greedy algorithm / microblog search / association rule mining approach / mining / closed itemset mining / social networks / statistical summarizer systems / summarization algorithm / social network / search engine / hashtag processing / /

MarketIndex

set 50000 / /

Organization

University of Stuttgart / University of Tunis El Manar / Internal Revenue Service / Faculty of Sciences of Tunis / d’association / IDF / INEX / University of Carthage / Institute for Computational Linguistics / /

Person

Amina Zingla / Yahya Slimani / Paul Sabatier / Helmut Schmid / /

Position

representative / /

ProgrammingLanguage

php / /

ProvinceOrState

Maryland / /

PublishedMedium

Computational Linguistics / /

Technology

CHARM algorithm / greedy optimization algorithm / API / greedy algorithm / Data Mining / search engine / perl / summarization algorithm / /

URL

http /

SocialTag