Ontology matching with semantic verification

Yves R. Jean-Mary; E. Patrick Shironoshita; Mansur R. Kabuka

doi:10.1016/j.websem.2009.04.001

Ontology matching with semantic verification

Yves R. Jean-Mary, E. Patrick Shironoshita, Mansur R. Kabuka

Electrical and Computer Engineering

Research output: Contribution to journal › Article › peer-review

271 Scopus citations

Abstract

Automated Semantic Matching of Ontologies with Verification (ASMOV) is a novel algorithm that uses lexical and structural characteristics of two ontologies to iteratively calculate a similarity measure between them, derives an alignment, and then verifies it to ensure that it does not contain semantic inconsistencies. In this paper, we describe the ASMOV algorithm, and then present experimental results that measure its accuracy using the OAEI 2008 tests, and that evaluate its use with two different thesauri: WordNet, and the Unified Medical Language System (UMLS). These results show the increased accuracy obtained by combining lexical, structural and extensional matchers with semantic verification, and demonstrate the advantage of using a domain-specific thesaurus for the alignment of specialized ontologies.

Original language	English (US)
Pages (from-to)	235-251
Number of pages	17
Journal	Journal of Web Semantics
Volume	7
Issue number	3
DOIs	https://doi.org/10.1016/j.websem.2009.04.001
State	Published - Sep 2009

Keywords

Ontology
Ontology alignment
Ontology mapping
Ontology matching
UMLS

ASJC Scopus subject areas

Computer Networks and Communications
Software
Human-Computer Interaction

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title = "Ontology matching with semantic verification",

abstract = "Automated Semantic Matching of Ontologies with Verification (ASMOV) is a novel algorithm that uses lexical and structural characteristics of two ontologies to iteratively calculate a similarity measure between them, derives an alignment, and then verifies it to ensure that it does not contain semantic inconsistencies. In this paper, we describe the ASMOV algorithm, and then present experimental results that measure its accuracy using the OAEI 2008 tests, and that evaluate its use with two different thesauri: WordNet, and the Unified Medical Language System (UMLS). These results show the increased accuracy obtained by combining lexical, structural and extensional matchers with semantic verification, and demonstrate the advantage of using a domain-specific thesaurus for the alignment of specialized ontologies.",

keywords = "Ontology, Ontology alignment, Ontology mapping, Ontology matching, UMLS",

author = "Jean-Mary, {Yves R.} and Shironoshita, {E. Patrick} and Kabuka, {Mansur R.}",

note = "Funding Information: This research has been supported through grant No. 1R43RR018667-01A2 from the National Institutes of Health. The authors also wish to acknowledge Christian Meilicke from the University of Mannheim for performing the evaluation of the alignments obtained from the anatomy ontologies.",

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AU - Shironoshita, E. Patrick

AU - Kabuka, Mansur R.

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KW - Ontology alignment

KW - Ontology mapping

KW - Ontology matching

KW - UMLS

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