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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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Submitted on : Monday, April 26, 2010 - 2:29:14 AM
Last modification on : Thursday, April 22, 2021 - 3:33:07 AM
Long-term archiving on: : Tuesday, September 28, 2010 - 1:31:08 PM


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  • HAL Id : hal-00476279, version 1



Laurent Brisson, Martine Collard. How to Semantically Enhance a Data Mining Process?. Lecture Notes in Business Information Processing, Springer-Verlag, 2009, 13, pp.103-116. ⟨hal-00476279⟩



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