✦ LIBER ✦

Approximate reasoning applied to unsupervised database mining

✍ Scribed by Lawrence J. Mazlack

Book ID: 101260048
Publisher: John Wiley and Sons
Year: 1997
Tongue: English
Weight: 249 KB
Volume: 12
Category: Article
ISSN: 0884-8173
DOI: 10.1002/(sici)1098-111x(199705)12:5<391::aid-int3>3.0.co;2-i

No coin nor oath required. For personal study only.

✦ Synopsis

If you do not expect the unexpected, you will not find it''-Heraclitus (Greek philosopher) ''The smart thing is to prepare for the unexpected''-message found in a Berkeley fortune cookie ''People recognize what they already have a model for''-Plato (Greek philosopher) ''You see what you expect to see''-medical school aphorism 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.

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