Database mining by learned cognitive dissonance reduction
Lawrence J. Mazlack · Proceedings of IEEE 5th International Fuzzy Systems · 2002
A soft computing approach for unsupervised, reactive, database mining is used. This is to meet the broad goals of database mining of discovering noteworthy, unrecognized associations between database items. A novel approach is suggested for unsupervised search controlled by dissonance reduction. Both crisp and non-crisp data are subject to discovery. Issues involve: coherence measures, granularization, user intelligible results, unsupervised recognition of interesting results, and concept equivalent formation.