• DocumentCode
    2848954
  • Title

    Sentiment mining in WebFountain

  • Author

    Yi, Jeonghee ; Niblack, Wayne

  • Author_Institution
    IBM Almaden Res. Center, San Jose, CA, USA
  • fYear
    2005
  • fDate
    5-8 April 2005
  • Firstpage
    1073
  • Lastpage
    1083
  • Abstract
    WebFountain is a platform for very large-scale text analytics applications that allows uniform access to a wide variety of sources. It enables the deployment of a variety of document-level and corpus-level miners in a scalable manner, and feeds information that drives end-user applications through a set of hosted Web services. Sentiment (or opinion) mining is one of the most useful analyses for various end-user applications, such as reputation management. Instead of classifying the sentiment of an entire document about a subject, our sentiment miner determines sentiment of each subject reference using natural language processing techniques. In this paper, we describe the fully functional system environment and the algorithms, and report the performance of the sentiment miner. The performance of the algorithms was verified on online product review articles, and more general documents including Web pages and news articles.
  • Keywords
    Internet; data mining; information retrieval; natural languages; text analysis; Web service; WebFountain; corpus-level miner; document-level miner; end-user application; natural language processing; online product review article; reputation management; sentiment mining; text analytics application; Algorithm design and analysis; Application software; Data mining; Feeds; Information analysis; Large-scale systems; Natural language processing; Performance analysis; Web pages; Web services;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Engineering, 2005. ICDE 2005. Proceedings. 21st International Conference on
  • ISSN
    1084-4627
  • Print_ISBN
    0-7695-2285-8
  • Type

    conf

  • DOI
    10.1109/ICDE.2005.132
  • Filename
    1410217