An API for Multi-lingual Ontology Matching

7846

Authors

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Abstract

AbstractOntology matching consists of generating a set of correspondences between the entities of two ontologies. This process is seen as a solution to data heterogeneity in ontology-based applications, enabling the interoperability between them. However, existing matching systems are designed by assuming that the entities of both source and target ontologies are written in the same languages ( English, for instance). Multi-lingual ontology matching is an open research issue. This paper describes an API for multi-lingual matching that implements two strategies, direct translation-based and indirect. The first strategy considers direct matching between two ontologies (i.e., without intermediary ontologies), with the help of external resources, i.e., translations. The indirect alignment strategy, proposed by (Jung et al., 2009), is based on composition of alignments. We evaluate these strategies using simple string similarity based matchers and three ontologies written in English, French, and Portuguese, an extension of the OAEI benchmark test 206.

Keywords

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Full Content

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Labeled Text

AbstractOntology matching consists of generating a set of correspondences between the entities of two ontologies. This process is seen as a solution to data heterogeneity in ontology-based applications, enabling the interoperability between them. However, existing matching systems are designed by assuming that the entities of both source and target ontologies are written in the same languages ( English, for instance). Multi-lingual ontology matching is an open research issue. This paper describes an API for multi-lingual matching that implements two strategies, direct translation-based and indirect. The first strategy considers direct matching between two ontologies (i.e., without intermediary ontologies), with the help of external resources, i.e., translations. The indirect alignment strategy, proposed by (Jung et al., 2009), is based on composition of alignments. We evaluate these strategies using simple string similarity based matchers and three ontologies written in English, French, and Portuguese, an extension of the OAEI benchmark test 206.

Publication Details

Paper ID:
7846
Year:
2010
Publication:
TIPSTER
Publication Type:
conf
DOI:
nan