Approximate reasoning applied to unsupervised database mining

• Published in: International journal of intelligent systems Vol. 12; no. 5; pp. 391 - 414
• Main Author: Mazlack, Lawrence J.
• Format: Journal Article
• Language: English
• Published: New York Wiley Subscription Services, Inc., A Wiley Company 01.05.1997; Wiley
• Subjects: Algorithmics. Computability. Computer arithmetics; Applied sciences; Artificial intelligence; Computer science; control theory; systems; Exact sciences and technology; Information systems. Data bases; Learning and adaptive systems; Memory organisation. Data processing; Software; Theoretical computing; Uncertainty; Database query; Information system; Sharing; Intelligibility; Expert system; Coherence; Database; Knowledge base; Algorithm
• ISSN: 0884-8173; 1098-111X
• DOI: 10.1002/(SICI)1098-111X(199705)12:5<391::AID-INT3>3.0.CO;2-I

A computational approach is shown for unsupervised, reactive, database mining. This approach is dependent on soft computing techniques. Database mining seeks to discover noteworthy, unrecognized associations between database items. A novel approach is suggested for unsupervised search controlled by dissonance reduction. Both crisp and noncrisp data are subject to discovery. Another aspect of uncertainty is the metric that controls discovery. Issues involve: coherence measures, granularization, user intelligible results, unsupervised recognition of interesting results, and concept equivalent formation. © 1997 John Wiley & Sons, Inc.