Paper Info
Title
MoA: OWL ontology merging and alignment tool for the semantic web
Abstract
Ontology merging and alignment is one of the effective methods for ontology sharing and reuse on the Semantic Web. A number of ontology merging and alignment tools have been developed, many of those tools depend mainly on concept (dis)similarity measure derived from linguistic cues. We present in this paper a linguistic information based approach to ontology merging and alignment. Our approach is based on two observations: majority of concept names used in ontology are composed of multiple-word combinations, and ontologies designed independently are, in most cases, organized in very different hierarchical structure even though they describe overlapping domains. These observations led us to a merging and alignment algorithm that utilizes both the local and global meaning of a concept. We devised our proposed algorithm in MoA, an OWL DL ontology merging and alignment tool. We tested MoA on 3 ontology pairs, and human experts followed 93% of the MoA's suggestions.
Year
DOI
Venue
2005
10.1007/11504894_100
IEA/AIE
Keywords
Field
DocType
ontology pair,ontology sharing,owl ontology,owl dl ontology,alignment tool,concept name,semantic web,linguistic cue,proposed algorithm,alignment algorithm,linguistic information
Ontology merging,Ontology (information science),Data mining,Ontology-based data integration,Ontology alignment,Information retrieval,Process ontology,Computer science,OWL-S,Suggested Upper Merged Ontology,Upper ontology
Conference
Volume
ISSN
ISBN
3533
0302-9743
3-540-26551-1
Citations 
PageRank 
References 
12
0.66
8
Authors
5
Name
Order
Citations
PageRank
Jaehong Kim138341.59
Minsu Jang210211.99
Young-Guk Ha313021.82
Joo-Chan Sohn415413.83
Sang Jo Lee5202.01