Automatic Detection of Duplicated Attributes in Ontology
- 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.
Author: | Irina Astrova, Arne KoschelORCiDGND |
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URN: | urn:nbn:de:bsz:960-opus4-35295 |
DOI: | https://doi.org/10.25968/opus-3529 |
DOI original: | https://doi.org/10.5220/0001961102830286 |
ISBN: | 978-989-8111-84-5 |
ISSN: | 2184-4992 |
Parent Title (English): | Proceedings of the 11th International Conference on Enterprise Information |
Publisher: | SciTePress |
Document Type: | Conference Proceeding |
Language: | English |
Year of Completion: | 2009 |
Publishing Institution: | Hochschule Hannover |
Release Date: | 2025/02/14 |
Tag: | Context-based similarity; Duplicated attributes; ICD algorithm; Market basket analysis; Ontology-based data integration |
GND Keyword: | OntologieGND; Semantische UnbestimmtheitGND; DuplikaterkennungGND; DatenbankGND; DatenqualitätGND; DatenintegrationGND |
Page Number: | 4 |
First Page: | 283 |
Last Page: | 286 |
Link to catalogue: | 1920168958 |
Institutes: | Fakultät IV - Wirtschaft und Informatik |
DDC classes: | 004 Informatik |
Licence (German): | ![]() |