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arXiv · 0910.0349

Post-Processing of Discovered Association Rules Using Ontologies

Claudia Marinica·Fabrice Guillet·Henri Briand
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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.

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Claudia Marinica, Fabrice Guillet, Henri Briand. 2009-10-02. Post-Processing of Discovered Association Rules Using Ontologies. https://doi.org/10.1109/icdmw.2008.87

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