Interactive visual exploration of association rules with rule-focusing methodology |
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Authors: | Julien Blanchard Fabrice Guillet Henri Briand |
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Affiliation: | (1) Département Informatique, école Polytechnique de l’Université de Nantes, La Chantrerie, BP 50609, 3 Nantes Cedex, 44306, France |
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Abstract: | On account of the enormous amounts of rules that can be produced by data mining algorithms, knowledge post-processing is a
difficult stage in an association rule discovery process. In order to find relevant knowledge for decision making, the user
(a decision maker specialized in the data studied) needs to rummage through the rules. To assist him/her in this task, we
here propose the rule-focusing methodology, an interactive methodology for the visual post-processing of association rules. It allows the user to explore
large sets of rules freely by focusing his/her attention on limited subsets. This new approach relies on rule interestingness
measures, on a visual representation, and on interactive navigation among the rules. We have implemented the rule-focusing
methodology in a prototype system called ARVis. It exploits the user's focus to guide the generation of the rules by means of a specific constraint-based rule-mining algorithm.
Julien Blanchard earned the Ph.D. in 2005 from Nantes University (France) and is currently an assistant professor at the Polytechnic School
of Nantes University. He is the author of a book chapter and seven journal and international conference papers in the field
of visualization and interestingness measures for data mining.
Fabrice Guillet is currently a member of the LINA laboratory (CNRS 2729) at the Polytechnic Graduate School of Nantes University (France).
He receive the Ph.D. degree in computer science in 1995 from the Ecole Nationale Supěrieure des Télécommunications de Bretagne.
He is author of 35 international publications in data mining and knowledge management. He is a founder and a permanent member
of the Steering Committee of the annual EGC French-speaking conference.
Henri Briand received the Ph.D. degree in 1983 from Paul Sabatier University located in Toulouse (France) and has published works in over
100 publications in database systems and database mining. He was the head of the Computer Engineering Department at the Polytechnic
School of Nantes University. He was in charge of a research team in the data mining domain. He is responsible for the organization
of the Data Mining Master in Nantes University. |
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Keywords: | Knowledge discovery in databases Association rules Post-processing Interactive visualization Rule focusing Constraint-based mining Interestingness measures Neighborhood of rules |
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