OBJECTMINER: A NEW APPROACH FOR MINING COMPLEX OBJECTS

Roxana Danger, José Ruíz-Shulcloper, Rafael Berlanga

2004

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.

Paper Citation

in Harvard Style

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, pages 42-47. DOI: 10.5220/0002633500420047

in Bibtex Style

@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},
}

in EndNote Style

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
AU - Danger R.
AU - Ruíz-Shulcloper J.
AU - Berlanga R.
PY - 2004
SP - 42
EP - 47
DO - 10.5220/0002633500420047