Korean Twitter Emotion Classification Using Automatically Built Emotion Lexicons and Fine-Grained Features

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 450
  • Download : 78
DC FieldValueLanguage
dc.contributor.authorDo, Hyo Jinko
dc.contributor.authorChoi, Ho Jinko
dc.date.accessioned2016-04-18T04:50:57Z-
dc.date.available2016-04-18T04:50:57Z-
dc.date.created2015-11-20-
dc.date.created2015-11-20-
dc.date.issued2015-10-30-
dc.identifier.citationthe 29th Pacific Asia Conference on Language, Information and Computation (PACLIC 29)-
dc.identifier.urihttp://hdl.handle.net/10203/204238-
dc.languageEnglish-
dc.publisherDeparment of Computer Science and Engineering Shanghai Jiao Tong University-
dc.titleKorean Twitter Emotion Classification Using Automatically Built Emotion Lexicons and Fine-Grained Features-
dc.typeConference-
dc.identifier.scopusid2-s2.0-84967104294-
dc.type.rimsCONF-
dc.citation.publicationnamethe 29th Pacific Asia Conference on Language, Information and Computation (PACLIC 29)-
dc.identifier.conferencecountryCC-
dc.identifier.conferencelocationHaoran High-Tech Mansion, Shanghai-
dc.embargo.liftdate9999-12-31-
dc.embargo.terms9999-12-31-
dc.contributor.localauthorChoi, Ho Jin-
dc.contributor.nonIdAuthorDo, Hyo Jin-
Appears in Collection
CS-Conference Papers(학술회의논문)
Files in This Item

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0