• DocumentCode
    2677000
  • Title

    Data Mining from an Al Perspective

  • Author

    Quinlan, R.

  • Author_Institution
    University of New South Wales, Sydney
  • fYear
    1999
  • fDate
    23-26 March 1999
  • Firstpage
    186
  • Lastpage
    186
  • Abstract
    Summary form only given, as follows. Data Mining, or Knowledge Discovery in Databases as it is also called, is claimed as an offspring by three disciplines: databases, statistics, and the machine learning subfield of artificial intelligence. (The term originated in statistics with distinctly pejorative overtones - data mining was characterized as fossicking in data without a guiding model.) Statistics is obviously relevant because that field has always focused on construction of models from data. Databases, too, is clearly central because current applications of data mining can involve very large corpora of information that are not necessarily in flat file form. So what??s left to be claimed by artificial intelligence and, in particular, machine learning? This talk will provide a definitely non-impartial answer to this question from the standpoint of a long-time ML practitioner.
  • Keywords
    Artificial intelligence; Australia; Biographies; Computer science; Data mining; Databases; Machine learning; Machine learning algorithms; Magnetic heads; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Engineering, 1999. Proceedings., 15th International Conference on
  • Conference_Location
    Sydney, NSW, Australia
  • ISSN
    1063-6382
  • Print_ISBN
    0-7695-0071-4
  • Type

    conf

  • DOI
    10.1109/ICDE.1999.754923
  • Filename
    754923