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Authors: Irina Astrova 1 and Arne Koschel 2

Affiliations: 1 Tallinn University of Technology, Estonia ; 2 University of Applied Sciences and Arts, Germany

ISBN: 978-989-8111-84-5

Keyword(s): Ontology-based data integration, Duplicated attributes, Context-based similarity, Market basket analysis, ICD algorithm.

Related Ontology Subjects/Areas/Topics: Coupling and Integrating Heterogeneous Data Sources ; Databases and Information Systems Integration ; Enterprise Information Systems

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.

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Paper citation in several formats:
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

@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},
}

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

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