• DocumentCode
    1175618
  • Title

    Guest Editors´ Introduction: Mining Actionable Knowledge on the Web

  • Author

    Yang, Qiang ; Knoblock, Craig A. ; Wu, Xindong

  • Volume
    19
  • Issue
    6
  • fYear
    2004
  • Firstpage
    30
  • Lastpage
    31
  • Abstract
    The Web-its resources and users-offers a wealth of information for data mining and knowledge discovery. Up to now, a great deal of work has been done applying data mining and machine learning methods to discover novel and useful knowledge on the Web. However, many techniques aim only at extracting knowledge for human users to view and use. Recently, more and more work addresses Web for knowledge that computer systems will use. You can apply such actionable knowledge back to the Web for measurable performance improvements. This special issue of IEEE Intelligent Systems features five articles that address the problem of actionable Web mining.
  • Keywords
    World Wide Web; actionable knowledge; collaborative filtering; content-based image retrieval; crawler; data mining; information extraction; Clustering algorithms; Collaboration; Crawlers; Data mining; Filtering algorithms; Humans; Information filtering; Information filters; Web mining; Web pages; World Wide Web; actionable knowledge; collaborative filtering; content-based image retrieval; crawler; data mining; information extraction;
  • fLanguage
    English
  • Journal_Title
    Intelligent Systems, IEEE
  • Publisher
    ieee
  • ISSN
    1541-1672
  • Type

    jour

  • DOI
    10.1109/MIS.2004.64
  • Filename
    1363731