Post-Processing of Discovered Association Rules Using Ontologies

Authors:
Claudia Marinica;Fabrice Guillet;Henri Briand
Affiliations:
-;-;-
Venue:
ICDMW '08 Proceedings of the 2008 IEEE International Conference on Data Mining Workshops
Year:
2008

Citing 0
Cited 1

Toward intelligent data warehouse mining: An ontology-integrated approach for multi-dimensional association mining

Expert Systems with Applications: An International Journal

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Abstract

In Data Mining, the usefulness of association rules is strongly limited by the huge amount of delivered rules. In this paper we propose a new approach to prune and filter discovered rules. Using Domain Ontologies, we strengthen the integration of user knowledge in the post-processing task. Furthermore, an interactive and iterative framework is designed to assist the user along the analyzing task. On the one hand, we represent user domain knowledge using a Domain Ontology over database. On the other hand, a novel technique is suggested to prune and to filter discovered rules. The proposed framework was applied successfully over the client database provided by Nantes Habitat.