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Authors: Xuan-Hiep Huynh ; Fabrice Guillet and Henri Briand

Affiliation: LINA CNRS FRE 2729 - Polytechnic school of Nantes university, France

Keyword(s): Interestingness measure, intensity of implication, cluster, objective measure, interestingness property.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Data Engineering ; Data Mining ; Databases and Information Systems Integration ; Datamining ; Enterprise Information Systems ; Health Information Systems ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: Selecting interestingness measures has been an important problem in knowledge discovery in database. A lot of measures have been proposed to extract the knowledge from large databases and many authors have introduced the interestingness properties for selecting a suitable measure for a given application. Some measures are adequate for some applications but the others are not, and it is difficult to capture what the best measures for a given data set are. In this paper, we present a new approach implemented in a tool to select the groups or clusters of objective interestingness measures that are highly correlated in an application. The final goal relies on helping the user to select the subset of measures that is the best adapted to discover the best rules according to his/her preferences.

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Paper citation in several formats:
Huynh, X.; Guillet, F. and Briand, H. (2005). CLUSTERING INTERESTINGNESS MEASURES WITH POSITIVE CORRELATION. In Proceedings of the Seventh International Conference on Enterprise Information Systems - Volume 2: ICEIS; ISBN 972-8865-19-8; ISSN 2184-4992, SciTePress, pages 248-253. DOI: 10.5220/0002508502480253

@conference{iceis05,
author={Xuan{-}Hiep Huynh. and Fabrice Guillet. and Henri Briand.},
title={CLUSTERING INTERESTINGNESS MEASURES WITH POSITIVE CORRELATION},
booktitle={Proceedings of the Seventh International Conference on Enterprise Information Systems - Volume 2: ICEIS},
year={2005},
pages={248-253},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002508502480253},
isbn={972-8865-19-8},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the Seventh International Conference on Enterprise Information Systems - Volume 2: ICEIS
TI - CLUSTERING INTERESTINGNESS MEASURES WITH POSITIVE CORRELATION
SN - 972-8865-19-8
IS - 2184-4992
AU - Huynh, X.
AU - Guillet, F.
AU - Briand, H.
PY - 2005
SP - 248
EP - 253
DO - 10.5220/0002508502480253
PB - SciTePress

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