ArticleWeb semantics (Online)2009
Ontology Matching with Semantic Verification.
Article in Web semantics (Online), 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Matching Biomedical Ontologies: Construction of Matching Clues and Systematic Evaluation of Different Combinations of Matchers.JMIR medical informatics · 2021Article
- FTRLIM: Distributed Instance Matching Framework for Large-Scale Knowledge Graph Fusion.Entropy (Basel, Switzerland) · 2021Article
- Matching sensor ontologies through siamese neural networks without using reference alignment.PeerJ. Computer science · 2021Article
- Optimizing Sensor Ontology Alignment through Compact co-Firefly Algorithm.Sensors (Basel, Switzerland) · 2020Article
- Tackling the challenges of matching biomedical ontologies.Journal of biomedical semantics · 2018Article
- Experiences from the anatomy track in the ontology alignment evaluation initiative.Journal of biomedical semantics · 2017Review
- An adaptive semantic based mediation system for data interoperability among Health Information Systems.Journal of medical systems · 2014Article
- Ontology alignment architecture for semantic sensor Web integration.Sensors (Basel, Switzerland) · 2013Article
- A semi-automatic semantic method for mapping SNOMED CT concepts to VCM Icons.Studies in health technology and informatics · 2013Article
- A gene ontology inferred from molecular networks.Nature biotechnology · 2013Article
- Logic-based assessment of the compatibility of UMLS ontology sources.Journal of biomedical semantics · 2011Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
ASMOV (Automated Semantic Matching of Ontologies with Verification) 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.