AN ONTOLOGY DRIVEN DATA MINING PROCESS

Laurent Brisson, Martine Collard

Abstract

This paper deals with knowledge integration in a data mining process. We suggest to model domain knowledge during business understanding and data understanding steps in order to build an ontology driven information system (ODIS). We present the KEOPS Methodology based on this approach. In KEOPS, the ODIS is dedicated to data mining tasks. It allows using expert knowledge for efficient data selection, data preparation and model interpretation. In this paper, we detail each of these ontology driven steps and we define a part-way interestingness measure that integrates both objective and subjective criteria in order to evaluate model relevance according to expert knowledge.

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Paper Citation


in Harvard Style

Brisson L. and Collard M. (2008). AN ONTOLOGY DRIVEN DATA MINING PROCESS . In Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8111-37-1, pages 54-61. DOI: 10.5220/0001697400540061


in Bibtex Style

@conference{iceis08,
author={Laurent Brisson and Martine Collard},
title={AN ONTOLOGY DRIVEN DATA MINING PROCESS},
booktitle={Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2008},
pages={54-61},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001697400540061},
isbn={978-989-8111-37-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - AN ONTOLOGY DRIVEN DATA MINING PROCESS
SN - 978-989-8111-37-1
AU - Brisson L.
AU - Collard M.
PY - 2008
SP - 54
EP - 61
DO - 10.5220/0001697400540061