An Efficient Method for Post Analysis of Patterns

R. Kuusik, I. Liiv, and G. Lind (Estonia)


Pattern post analysis, data mining, generator of hypotheses, and monotone system theory


Finding and extracting frequent patterns is one of the most important tasks in data mining, therefore various algorithms have been introduced over time. Unfortunately, when the sizes of datasets increase, completely different and new problems arise. Even if we are able to extract the IF...THEN rules in reasonable time, it is possible that the algorithms will find millions of patterns. Interpretation of all of them would be a grievous baffling problem for even a team of analysts. In this paper we describe a method we have used for post-analysis of patterns. The basic idea is presented with an example and the rules for result transformation are given, making it possible to apply standard querying tools. Although we have implemented it as an extension to the generator of hypotheses, it would also give reasonable results with other rule extracting methods.

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