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Volumn , Issue , 2010, Pages 1685-1688

Learning sentiment classification model from labeled features

Author keywords

Generalized expectation; Opinion mining; Self learned features; Sentiment analysis; Weakly supervised classification

Indexed keywords

GENERALIZED EXPECTATION; OPINION MINING; SELF-LEARNED FEATURES; SENTIMENT ANALYSIS; SUPERVISED CLASSIFICATION;

EID: 78651271277     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1871437.1871704     Document Type: Conference Paper
Times cited : (6)

References (11)
  • 1
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    • When specialists and generalists work together: Overcoming domain dependence in sentiment tagging
    • A. Andreevskaia and S. Bergler. When specialists and generalists work together: Overcoming domain dependence in sentiment tagging. In ACL-HLT, pages 290-298, 2008.
    • (2008) ACL-HLT , pp. 290-298
    • Andreevskaia, A.1    Bergler, S.2
  • 2
    • 77956543198 scopus 로고    scopus 로고
    • Topic-wise, sentiment-wise, or otherwise? Identifying the hidden dimension for unsupervised text classification
    • S. Dasgupta and V. Ng. Topic-wise, Sentiment-wise, or Otherwise? Identifying the Hidden Dimension for Unsupervised Text Classification. In EMNLP, pages 580-589, 2009.
    • (2009) EMNLP , pp. 580-589
    • Dasgupta, S.1    Ng, V.2
  • 3
    • 57349122015 scopus 로고    scopus 로고
    • Learning from labeled features using generalized expectation criteria
    • G. Druck, G. Mann, and A. McCallum. Learning from labeled features using generalized expectation criteria. In SIGIR, pages 595-602, 2008.
    • (2008) SIGIR , pp. 595-602
    • Druck, G.1    Mann, G.2    McCallum, A.3
  • 4
    • 78651345514 scopus 로고    scopus 로고
    • A non-negative matrix tri-factorization approach to sentiment classification with lexical prior knowledge
    • T. Li, Y. Zhang, and V. Sindhwani. A non-negative matrix tri-factorization approach to sentiment classification with lexical prior knowledge. In ACL-IJCNLP, pages 244-252, 2009.
    • (2009) ACL-IJCNLP , pp. 244-252
    • Li, T.1    Zhang, Y.2    Sindhwani, V.3
  • 5
    • 79957604857 scopus 로고    scopus 로고
    • A comparative study of Bayesian models for unsupervised sentiment detection
    • C. Lin, Y. He, and R. Everson. A Comparative Study of Bayesian Models for Unsupervised Sentiment Detection. In CoNLL, 2010.
    • (2010) CoNLL
    • Lin, C.1    He, Y.2    Everson, R.3
  • 7
    • 70350645448 scopus 로고    scopus 로고
    • Sentiment analysis of blogs by combining lexical knowledge with text classification
    • P. Melville, W. Gryc, and R. D. Lawrence. Sentiment analysis of blogs by combining lexical knowledge with text classification. In KDD, pages 1275-1284, 2009.
    • (2009) KDD , pp. 1275-1284
    • Melville, P.1    Gryc, W.2    Lawrence, R.D.3
  • 8
    • 74549201048 scopus 로고    scopus 로고
    • Selc: A self-supervised model for sentiment classification
    • L. Qiu, W. Zhang, C. Hu, and K. Zhao. Selc: a self-supervised model for sentiment classification. In CIKM, pages 929-936, 2009.
    • (2009) CIKM , pp. 929-936
    • Qiu, L.1    Zhang, W.2    Hu, C.3    Zhao, K.4
  • 10
    • 57349091686 scopus 로고    scopus 로고
    • Combining learn-based and lexicon-based techniques for sentiment detection without using labeled examples
    • S. Tan, Y. Wang, and X. Cheng. Combining learn-based and lexicon-based techniques for sentiment detection without using labeled examples. In SIGIR, pages 743-744, 2008.
    • (2008) SIGIR , pp. 743-744
    • Tan, S.1    Wang, Y.2    Cheng, X.3
  • 11
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    • Automatic seed word selection for unsupervised sentiment classification of Chinese text
    • T. Zagibalov and J. Carroll. Automatic seed word selection for unsupervised sentiment classification of Chinese text. In COLING, pages 1073-1080, 2008.
    • (2008) COLING , pp. 1073-1080
    • Zagibalov, T.1    Carroll, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.