Ontology Matching based on Multi-Aspect Consensus Clustering of Communities

André Ippolito, Jorge Rady de Almeida Júnior

2016

Abstract

With the increase in the number of existing ontologies, ontology integration becomes a challenging task. A fundamental step in ontology integration is ontology matching, which is the process of finding correspondences between elements of different ontologies. For large-scale ontology matching, some authors developed a divide-and-conquer strategy, which partitions ontologies, clusters similar partitions and restricts the matching process to ontology elements of similar partitions. Works related to this strategy considered only a single ontology aspect for clustering. In this paper, we proposed a solution for ontology matching based on Bayesian Cluster Ensembles (BCE) of multiple aspects of ontology partitions. We partition ontologies applying Community Detection techniques. We believe that BCE of multiple aspects of ontology partitions can provide an ontology clustering that is more precise than the clustering of a single aspect. This can result in a more precise matching.

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Paper Citation


in Harvard Style

Ippolito A. and Júnior J. (2016). Ontology Matching based on Multi-Aspect Consensus Clustering of Communities . In Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-187-8, pages 321-326. DOI: 10.5220/0005893103210326


in Bibtex Style

@conference{iceis16,
author={André Ippolito and Jorge Rady de Almeida Júnior},
title={Ontology Matching based on Multi-Aspect Consensus Clustering of Communities},
booktitle={Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2016},
pages={321-326},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005893103210326},
isbn={978-989-758-187-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - Ontology Matching based on Multi-Aspect Consensus Clustering of Communities
SN - 978-989-758-187-8
AU - Ippolito A.
AU - Júnior J.
PY - 2016
SP - 321
EP - 326
DO - 10.5220/0005893103210326