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
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