Publication Date:
2013-05-23
Description:
Ontology matching is a crucial issue in the domain of semantic web and data interoperability. In this paper, a core word based method for measuring similarity from the semantic level of ontology entities is described. In ontology, most labels of entities are compound words rather than single meaningful words. However, the main meaning is represented usually by one word of them, which is called core word. The core word is learned by investigating certain patterns, which are defined based on part of speech (POS) and linguistics knowledge. The other information is noted as complementary information. An algorithm is given to measure the similarity between a pair of compound words and short texts. In order to support diverse situation, especially when core words cannot be recognized, non semantic based ontology matching techniques are applied from lexical and structural level of ontology. The described method is tested on real ontology and benchmarking data sets. It showed good matching ability and obtained promising results. Content Type Journal Article Pages 167-176 DOI 10.3233/KES-130270 Authors Fuqi Song, University Bordeaux, IMS UMR, Talence, France Gregory Zacharewicz, University Bordeaux, IMS UMR, Talence, France David Chen, University Bordeaux, IMS UMR, Talence, France Journal International Journal of Knowledge-Based and Intelligent Engineering Systems Online ISSN 1875-8827 Print ISSN 1327-2314 Journal Volume Volume 17 Journal Issue Volume 17, Number 2 / 2013
Print ISSN:
1327-2314
Electronic ISSN:
1875-8827
Topics:
Computer Science
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