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GraphMatcher: A Graph Representation Learning Approach for Ontology Matching

Artificial Intelligence 2024-04-24 v1

Abstract

Ontology matching is defined as finding a relationship or correspondence between two or more entities in two or more ontologies. To solve the interoperability problem of the domain ontologies, semantically similar entities in these ontologies must be found and aligned before merging them. GraphMatcher, developed in this study, is an ontology matching system using a graph attention approach to compute higher-level representation of a class together with its surrounding terms. The GraphMatcher has obtained remarkable results in in the Ontology Alignment Evaluation Initiative (OAEI) 2022 conference track. Its codes are available at ~\url{https://github.com/sefeoglu/gat_ontology_matching}.

Keywords

Cite

@article{arxiv.2404.14450,
  title  = {GraphMatcher: A Graph Representation Learning Approach for Ontology Matching},
  author = {Sefika Efeoglu},
  journal= {arXiv preprint arXiv:2404.14450},
  year   = {2024}
}

Comments

The 17th International Workshop on Ontology Matching, The 21st International Semantic Web Conference (ISWC) 2022, 23 October 2022, Hangzhou, China

R2 v1 2026-06-28T16:02:42.713Z