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Volumn , Issue , 2004, Pages

Sentiment classification on customer feedback data: Noisy data, large feature vectors, and the role of linguistic analysis

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL LINGUISTICS; SUPPORT VECTOR MACHINES;

EID: 84872201395     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (300)

References (19)
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  • 2
    • 0031361611 scopus 로고    scopus 로고
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    • Thomas G. Dietterich (1997): “Machine-learning research: Four current directions”. In: AI Magazine, 18 (4), pp.97-136.
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    • Dietterich, Thomas G.1
  • 4
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    • Accurate Methods for the Statistics of Surprise and Coincidence
    • Ted Dunning. 1993. Accurate Methods for the Statistics of Surprise and Coincidence. Computational Linguistics 19: 61-74.
    • (1993) Computational Linguistics , vol.19 , pp. 61-74
    • Dunning, Ted1
  • 6
    • 85119093321 scopus 로고    scopus 로고
    • Linguistic correlates of style: authorship classification with deep linguistic analysis features
    • Paper to be presented at
    • Michael Gamon (2004): “Linguistic correlates of style: authorship classification with deep linguistic analysis features”. Paper to be presented at COLING 2004.
    • (2004) COLING 2004
    • Gamon, Michael1
  • 7
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    • Intelligent Writing Assistance
    • R. Dale, H. Moisl and H. Somers, eds., Marcel Dekker
    • George Heidorn. (2000): “Intelligent Writing Assistance.” In R. Dale, H. Moisl and H. Somers, eds., Handbook of Natural Language Processing. Marcel Dekker.
    • (2000) Handbook of Natural Language Processing
    • Heidorn, George1
  • 8
    • 84957069814 scopus 로고    scopus 로고
    • Text Categorization with Support Vector Machines: Learning with Many Relevant Features
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    • (1998) Proceedings of ECML 1998 , pp. 137-142
    • Joachims, Thorsten1
  • 13
    • 0003120218 scopus 로고    scopus 로고
    • Fast training of SVMs using sequential minimal optimization
    • B. Schoelkopf, C. Burges and A. Smola (eds) MIT Press, Cambridge, MA
    • John Platt (1999): “Fast training of SVMs using sequential minimal optimization”. In: B. Schoelkopf, C. Burges and A. Smola (eds.) “Advances in Kernel Methods: Support Vector Learning”, MIT Press, Cambridge, MA, pp. 185-208.
    • (1999) Advances in Kernel Methods: Support Vector Learning , pp. 185-208
    • Platt, John1
  • 15
    • 0037365188 scopus 로고    scopus 로고
    • Combining Classifiers with Meta Decision Trees
    • Ljupčo Todorovski and Sašo Džeroski (2003): “Combining Classifiers with Meta Decision Trees”. In: Machine Learning, 50, pp.223-249.
    • (2003) Machine Learning , vol.50 , pp. 223-249
    • Todorovski, Ljupčo1    Džeroski, Sašo2
  • 16
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    • Thumbs up or thumbs down? Semantic orientation applied to unsupervised classification of reviews
    • Peter D. Turney (2002): “Thumbs up or thumbs down? Semantic orientation applied to unsupervised classification of reviews”. In: Proceedings of ACL 2002, pp. 417-424.
    • (2002) Proceedings of ACL 2002 , pp. 417-424
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  • 17
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    • Unsupervised lLearning of Semantic Orientation from a Hundred-Billion-Word Corpus
    • Technical report ERC-1094 (NRC 44929), National research Council of Canada
    • Peter D. Turney and M. L. Littman (2002): “Unsupervised lLearning of Semantic Orientation from a Hundred-Billion-Word Corpus.” Technical report ERC-1094 (NRC 44929), National research Council of Canada.
    • (2002)
    • Turney, Peter D.1    Littman, M. L.2
  • 19
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    • Towards Answering pinion Questions: Separating Facts from Opinions and Identifying the Polarity of Opinion Sentences
    • Hong Yu and Vasileios Hatzivassiloglou (2003): “Towards Answering pinion Questions: Separating Facts from Opinions and Identifying the Polarity of Opinion Sentences”. In: Proceedings of EMNLP 2003.
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    • Yu, Hong1    Hatzivassiloglou, Vasileios2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.