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Authors: Claudia Marinica 1 ; Andrei Olaru 2 and Fabrice Guillet 1

Affiliations: 1 Ecole Polytechnique del’Universite de Nantes, France ; 2 University Politehnica of Bucharest and Ecole Polytechnique del’Universite de Nantes, Romania

Keyword(s): Association Rules, Mining Algorithms, User-Driven Mining, Rule Interestingness, Subjective Measures.

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 ; Human-Computer Interaction ; Sensor Networks ; Signal Processing ; Soft Computing ; User Needs

Abstract: One of the main issues in the process of Knowledge Discovery in Databases is the Mining of Association Rules. Although a great variety of pattern mining algorithms have been designed to this purpose, their main problems rely on in the large number of extracted rules, that need to be filtered in a post-processing step resulting in fewer but more interesting results. In this paper we suggest a new algorithm, that allows the user to explore the rules space locally and incrementally. The user interests and preferences are represented by means of the new proposed formalism - the Rule Schemas. The method has been successfully tested on the database provided by Nantes Habitat.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Marinica, C.; Olaru, A. and Guillet, F. (2009). USER-DRIVEN ASSOCIATION RULE MINING USING A LOCAL ALGORITHM. In Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS; ISBN 978-989-8111-85-2; ISSN 2184-4992, SciTePress, pages 200-205. DOI: 10.5220/0002003002000205

@conference{iceis09,
author={Claudia Marinica. and Andrei Olaru. and Fabrice Guillet.},
title={USER-DRIVEN ASSOCIATION RULE MINING USING A LOCAL ALGORITHM},
booktitle={Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS},
year={2009},
pages={200-205},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002003002000205},
isbn={978-989-8111-85-2},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS
TI - USER-DRIVEN ASSOCIATION RULE MINING USING A LOCAL ALGORITHM
SN - 978-989-8111-85-2
IS - 2184-4992
AU - Marinica, C.
AU - Olaru, A.
AU - Guillet, F.
PY - 2009
SP - 200
EP - 205
DO - 10.5220/0002003002000205
PB - SciTePress

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