Aspects of approximate reasoning applied to unsupervised database mining

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 data items in a database. Both crisp and non-crisp data are subject to discovery. Another aspect of uncertainty is the metric that controls discovery. Research issues involve: coherence measures, granularization, user intelligible results, unsupervised recognition of interesting results, and concept formation