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
Link To Document :
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