
Traditional framework for mining association rules has pointed out the derivation of many redundant rules, in order to be reliable in a decision making process, such discovered rules have to be concise and easily understandable for users or as well as an input to visualization tools. We present a 3D histograms-based visualization prototype for handling generic bases of association rules. An interesting feature of the prototype is that it provides a "contextual" exploration of such rule set. Such additional displayed knowledge, based on the construction of fuzzy meta-rules, enhances man-machine interaction by emulating a cooperative behavior.
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