MIME: a framework for interactive visual pattern mining

Authors:
Bart Goethals;Sandy Moens;Jilles Vreeken
Affiliations:
University of Antwerp, Belgium;University of Antwerp, Belgium;University of Antwerp, Belgium
Venue:
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III
Year:
2011

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Abstract

We present a framework for interactive visual pattern mining. Our system enables the user to browse through the data and patterns easily and intuitively, using a toolbox consisting of interestingness measures, mining algorithms and post-processing algorithms to assist in identifying interesting patterns. By mining interactively, we enable the user to combine their subjective interestingness measure and background knowledge with a wide variety of objective measures to easily and quickly mine the most important and interesting patterns. Basically, we enable the user to become an essential part of the mining algorithm. Our demo currently applies to mining interesting itemsets and association rules, and its extension to episodes and decision trees is ongoing research.