Post-Processing of Discovered Association Rules Using Ontologies
Pisa(2009)
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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Key words
data mining,ontologies (artificial intelligence),association rules,data mining,ontologies,association rules,data mining,knowledge management,ontologies,
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