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How to semantically enhance a data mining process?

Abstract : This paper presents the KEOPS data mining methodology centered on domain knowledge integration. KEOPS is a CRISP-DM compliant methodology which integrates a knowledge base and an ontology. In this paper, we focus first on the pre-processing steps of business understanding and data understanding in order to build an ontology driven information system (ODIS). Then we show how the knowledge base is used for the post-processing step of model interpretation. We detail the role of the ontology and we define a part-way interestingness measure that integrates both objective and subjective criteria in order to eval model relevance according to expert knowledge. We present experiments conducted on real data and their results.
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Contributor : Bibliothèque Télécom Bretagne <>
Submitted on : Monday, May 6, 2019 - 1:21:02 PM
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Laurent Brisson, Martine Collard. How to semantically enhance a data mining process?. Enterprise information systems, 19, Springer Berlin Heidelberg, pp.103 - 116, 2009, Lecture Notes in Business Information Processing, 978-3-642-00669-2. ⟨10.1007/978-3-642-00670-8_8⟩. ⟨hal-02121061⟩



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