Name
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. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1016/j.websem.2009.04.001 | J. Web Sem. |
Keywords | Field | DocType |
ontology mapping,umls,unified medical language system,ontology alignment,biomedical research,bioinformatics,ontology matching,ontology | Data mining,Semantic integration,Similarity measure,Computer science,Natural language processing,Artificial intelligence,WordNet,Semantic matching,Semantic similarity,Ontology (information science),Ontology alignment,Information retrieval,Unified Medical Language System | Journal |
Volume | Issue | ISSN |
7 | 3 | 1570-8268 |
Citations | PageRank | References |
111 | 3.32 | 26 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yves R. Jean-Mary | 1 | 124 | 5.47 |
| E. Patrick Shironoshita | 2 | 122 | 6.15 |
| Mansur R. Kabuka | 3 | 250 | 16.95 |