Enhancing Tutoring Intelligence Using Knowledge Discovery Techniques
WI-IATW '06 Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology
An interactive approach to display large sets of association rules
Proceedings of the 2007 conference on Human interface: Part I
IGB: a new informative generic base of association rules
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
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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 both concise and easily understandable for users, and/or as an input to visualization tools [ I ] . In this paper we present a graphical visualization prototype for handling generic bases of association rules. We discuss also the most adequate graphical visualization technique depending on the intrinsic structure of the generic bases of association rules. An interesting feature of the prototype is that it provides a "contextual" exploration of such rule set. Such exploration, based on the discovery of 驴 fuzzy meta-rules, enhances man-machine interaction by emulating a cooperative