CLUSTERING WITH GRANULAR INFORMATION PROCESSING

Urszula Kużelewska

2011

Abstract

Clustering is a part of data mining domain. Its task is to detect groups of similar objects on the basis of established similarity criterion. Granular computing (GrC) includes methods from various areas with the aim to support human with better understanding analyzed problem and generated results. Granular computing techniques create and/or process data portions named as granules identified with regard to similar description, functionality or behavior. Interesting characteristic of granular computation is offer of multi-perspective view of data depending on required resolution level. Data granules identified on different levels of resolution form a hierarchical structure expressing relations between objects of data. A method proposed in this article performs creation data granules by clustering data in form of hyperboxes. The results are compared with clustering of point-type data with regard to complexity, quality and interpretability.

Paper Citation

in Harvard Style

Kużelewska U. (2011). CLUSTERING WITH GRANULAR INFORMATION PROCESSING . In Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8425-40-9, pages 89-97. DOI: 10.5220/0003142700890097

in Bibtex Style

@conference{icaart11,
author={Urszula Kużelewska},
title={CLUSTERING WITH GRANULAR INFORMATION PROCESSING},
booktitle={Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2011},
pages={89-97},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003142700890097},
isbn={978-989-8425-40-9},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - CLUSTERING WITH GRANULAR INFORMATION PROCESSING
SN - 978-989-8425-40-9
AU - Kużelewska U.
PY - 2011
SP - 89
EP - 97
DO - 10.5220/0003142700890097