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Volumn , Issue , 2009, Pages 258-261

Delta TFIDF: An Improved Feature Space for Sentiment Analysis

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; DATA MINING; LEARNING SYSTEMS; SOCIAL NETWORKING (ONLINE);

EID: 85125402781     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1609/icwsm.v3i1.13979     Document Type: Conference Paper
Times cited : (244)

References (9)
  • 4
    • 0036161242 scopus 로고    scopus 로고
    • Text Categorization with Support Vector Machines. How to Represent Texts in Input Space?
    • Leopold, E., and Kindermann, J. 2002. Text Categorization with Support Vector Machines. How to Represent Texts in Input Space? Machine Learning 46(1):423-444.
    • (2002) Machine Learning , vol.46 , Issue.1 , pp. 423-444
    • Leopold, E.1    Kindermann, J.2
  • 5
    • 85141280473 scopus 로고    scopus 로고
    • A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts
    • Pang, B., and Lee, L. 2004. A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts. Proc. of the ACL 271-278.
    • (2004) Proc. of the ACL , pp. 271-278
    • Pang, B.1    Lee, L.2
  • 6
    • 85141803251 scopus 로고    scopus 로고
    • Thumbs up? sentiment classification using machine learning techniques
    • Pang, B.; Lee, L.; and Vaithyanathan, S. 2002. Thumbs up? sentiment classification using machine learning techniques. In Proc. of EMNLP 2002.
    • (2002) Proc. of EMNLP 2002
    • Pang, B.1    Lee, L.2    Vaithyanathan, S.3
  • 7
    • 80053357527 scopus 로고    scopus 로고
    • Get out the vote: Determining support or opposition from Congressional floor-debate transcripts
    • Thomas, M.; Pang, B.; and Lee, L. 2006. Get out the vote: Determining support or opposition from Congressional floor-debate transcripts. In Proc. of EMNLP, 327-335.
    • (2006) Proc. of EMNLP , pp. 327-335
    • Thomas, M.1    Pang, B.2    Lee, L.3
  • 9
    • 77957858975 scopus 로고    scopus 로고
    • Using Annotator Rationales to Improve Machine Learning for Text Categorization
    • Zaidan, O.; Eisner, J.; and Piatko, C. 2007. Using Annotator Rationales to Improve Machine Learning for Text Categorization. Proc. of NAACL HLT 260-267.
    • (2007) Proc. of NAACL HLT , pp. 260-267
    • Zaidan, O.1    Eisner, J.2    Piatko, C.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.