• DocumentCode
    3295481
  • Title

    Data mining on text

  • Author

    Clifton, Chris ; Steinheiser, Rick

  • Author_Institution
    Mitre Corp., Bedford, MA, USA
  • fYear
    1998
  • fDate
    19-21 Aug 1998
  • Firstpage
    630
  • Lastpage
    635
  • Abstract
    Data mining technology is giving us the ability to extract meaningful patterns from large quantities of structured data. Information retrieval systems have made large quantities of textual data available. Extracting meaningful patterns from this data is difficult. Current tools for mining structured data are inappropriate for free text. We outline problems involved in Knowledge Discovery in Text, and present an architecture for extracting patterns that hold across multiple documents. The capabilities that such a system could provide are illustrated
  • Keywords
    information retrieval; knowledge acquisition; very large databases; Knowledge Discovery in Text; data mining; multiple documents; structured data; textual data; Data engineering; Data mining; Database languages; Engines; Filters; Information retrieval; Marketing and sales; Mining industry; Text mining; US Department of Defense;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Software and Applications Conference, 1998. COMPSAC '98. Proceedings. The Twenty-Second Annual International
  • Conference_Location
    Vienna
  • ISSN
    0730-3157
  • Print_ISBN
    0-8186-8585-9
  • Type

    conf

  • DOI
    10.1109/CMPSAC.1998.716738
  • Filename
    716738