• DocumentCode
    1925956
  • Title

    The Unified Collocation Framework for Opinion Mining

  • Author

    Xia, Yun-qing ; Xu, Rui-Feng ; Wong, Kam-Fai ; Zheng, Fang

  • Author_Institution
    Tsinghua Univ., Beijing
  • Volume
    2
  • fYear
    2007
  • fDate
    19-22 Aug. 2007
  • Firstpage
    844
  • Lastpage
    850
  • Abstract
    Opinion mining is a complicated text understanding technology involving opinion extraction and sentiment analysis. State-of-the-art techniques adopt idea of attribute-driven or sentiment-driven, leading to low opinion mining coverage. This paper proposes the unified collocation framework (UCF) and describes a novel unified collocation-driven (UCD) opinion mining method. The UCF incorporates attribute-sentiment collocations as well as their syntactical features to achieve reasonable generalization ability. Preliminary experiments show that 0.245 on averages improve recall of opinion extraction without obvious loss on opinion extraction precision and sentiment analysis accuracy.
  • Keywords
    data mining; text analysis; attribute-sentiment collocation; low opinion mining coverage; opinion extraction; sentiment analysis; syntactical features; text understanding; unified collocation framework; unified collocation-driven opinion mining; Cybernetics; Data mining; Databases; Electronic mail; Machine learning; Manufacturing; Natural languages; Ontologies; Search engines; Speech analysis; Opinion extraction; Opinion mining; Sentiment analysis; Unified collocation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2007 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-0973-0
  • Electronic_ISBN
    978-1-4244-0973-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2007.4370260
  • Filename
    4370260