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Authors: Roxana Danger 1 ; José Ruíz-Shulcloper 2 and Rafael Berlanga 3

Affiliations: 1 University of Oriente, Cuba ; 2 Institute of Cybernetics, Mathematics and Physics, Cuba ; 3 Jaume I University, Spain

Keyword(s): Data-mining algorithms, Association rules, Complex objects.

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: Since their introduction in 1993, association rules have been successfully applied to the description and summarization of discovered relations between attributes in a large collection of objects. However, most of the research works in this area have focused on mining simple objects, usually represented as a set of binary variables. The proposed work presents a framework for mining complex objects, whose attributes can be of any data type (single and multi-valued). The mining process is guided by the semantics associated to each object feature, which is stated by users by providing both a comparison criterion and a similarity function over the object subdescriptions. Experimental results show the usefulness of the proposal.

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Paper citation in several formats:
Danger, R.; Ruíz-Shulcloper, J. and Berlanga, R. (2004). OBJECTMINER: A NEW APPROACH FOR MINING COMPLEX OBJECTS. In Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 2: ICEIS; ISBN 972-8865-00-7; ISSN 2184-4992, SciTePress, pages 42-47. DOI: 10.5220/0002633500420047

@conference{iceis04,
author={Roxana Danger. and José Ruíz{-}Shulcloper. and Rafael Berlanga.},
title={OBJECTMINER: A NEW APPROACH FOR MINING COMPLEX OBJECTS},
booktitle={Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 2: ICEIS},
year={2004},
pages={42-47},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002633500420047},
isbn={972-8865-00-7},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 2: ICEIS
TI - OBJECTMINER: A NEW APPROACH FOR MINING COMPLEX OBJECTS
SN - 972-8865-00-7
IS - 2184-4992
AU - Danger, R.
AU - Ruíz-Shulcloper, J.
AU - Berlanga, R.
PY - 2004
SP - 42
EP - 47
DO - 10.5220/0002633500420047
PB - SciTePress