How to Semantically Enhance a Data Mining Process? - Archive ouverte HAL Access content directly
Journal Articles Lecture Notes in Business Information Processing Year : 2009

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.
Fichier principal
Vignette du fichier
How_to_Semantically_Enhance_a_Data_Mining_Process_-_Brisson_et_al._-_LNBPI_2009.pdf (545.19 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-00476279 , version 1 (26-04-2010)

Identifiers

  • HAL Id : hal-00476279 , version 1

Cite

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

Share

Gmail Facebook Twitter LinkedIn More