• DocumentCode
    2335051
  • Title

    Closing the loop: heuristics for autonomous discovery

  • Author

    Livingston, Gary R. ; Rosenberg, John M. ; Buchanan, Bruce G.

  • Author_Institution
    Pittsburgh Univ., PA, USA
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    393
  • Lastpage
    400
  • Abstract
    Autonomous discovery systems will be able to peruse very large databases more thoroughly than people can. In a companion paper by G.R. Livingston et al. (see ibid., p.385-92, 2001), we describe a general framework for autonomous systems. We present and evaluate heuristics for use in this framework. Although these heuristics were designed for a prototype system, we believe they provide good initial solutions to problems encountered when implementing fully autonomous discovery systems. As such, these heuristics may be used as the starting point for future research into fully autonomous discovery systems
  • Keywords
    data mining; heuristic programming; very large databases; HAMB; autonomous discovery heuristics; autonomous discovery systems; domain-independent heuristics; domain-specific knowledge; justification based framework; rule-induction targets; very large databases; Buildings; Crystallization; Databases; Lungs; Minerals; Mining industry; Patient rehabilitation; Prototypes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining, 2001. ICDM 2001, Proceedings IEEE International Conference on
  • Conference_Location
    San Jose, CA
  • Print_ISBN
    0-7695-1119-8
  • Type

    conf

  • DOI
    10.1109/ICDM.2001.989544
  • Filename
    989544