AUTOMATIC DETECTION OF DUPLICATED ATTRIBUTES IN ONTOLOGY

Irina Astrova, Arne Koschel

Abstract

Semantic heterogeneity is the ambiguous interpretation of terms describing the meaning of data in heterogeneous data sources such as databases. This is a well-known problem in data integration. A recent solution to this problem is to use ontologies, which is called ontology-based data integration. However, ontologies can contain duplicated attributes, which can lead to improper integration results. This paper proposes a novel approach that analyzes a workload of queries over an ontology to automatically calculate (semantic) distances between attributes, which are then used for duplicate detection.

References

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Paper Citation


in Harvard Style

Astrova I. and Koschel A. (2009). AUTOMATIC DETECTION OF DUPLICATED ATTRIBUTES IN ONTOLOGY . In Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-8111-84-5, pages 283-286. DOI: 10.5220/0001961102830286


in Bibtex Style

@conference{iceis09,
author={Irina Astrova and Arne Koschel},
title={AUTOMATIC DETECTION OF DUPLICATED ATTRIBUTES IN ONTOLOGY},
booktitle={Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2009},
pages={283-286},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001961102830286},
isbn={978-989-8111-84-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - AUTOMATIC DETECTION OF DUPLICATED ATTRIBUTES IN ONTOLOGY
SN - 978-989-8111-84-5
AU - Astrova I.
AU - Koschel A.
PY - 2009
SP - 283
EP - 286
DO - 10.5220/0001961102830286