OWL2Vec4OA: Tailoring Knowledge Graph Embeddings for Ontology Alignment

Sevinj Teymurova, Ernesto Jiménez-Ruiz, Tillman Weyde, Jiaoyan Chen
8/12/2024
cs.AI

No official code found. Best implementation: Sevinjt/OWL2Vec4OA (3 stars, Apache-2.0, last commit 2025-07-26).

Abstract

Ontology alignment is integral to achieving semantic interoperability as the number of available ontologies covering intersecting domains is increasing. This paper proposes OWL2Vec4OA, an extension of the ontology embedding system OWL2Vec*. While OWL2Vec* has emerged as a powerful technique for ontology embedding, it currently lacks a mechanism to tailor the embedding to the ontology alignment task. OWL2Vec4OA incorporates edge confidence values from seed mappings to guide the random walk strategy. We present the theoretical foundations, implementation details, and experimental evaluation of our proposed extension, demonstrating its potential effectiveness for ontology alignment tasks.

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Code Implementations(1)

Sevinjt/OWL2Vec4OACommunity100%
Apache-2.0

OWL2Vec4OA is an extension of an ontology embedding system OWL2Vec*, which incorporate confidence values in the graph edges represented by (uncertain) available mappings between the network of ontologies

31Shell, PythonJul 31, 20241 years agoApache-2.0

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Cite this paper

@article{teymurova2024owlvecoa,
  title  = {OWL2Vec4OA: Tailoring Knowledge Graph Embeddings for Ontology Alignment},
  author = {Sevinj Teymurova and Ernesto Jiménez-Ruiz and Tillman Weyde and Jiaoyan Chen},
  year   = {2024},
  eprint = {2408.06310},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2408.06310v2}
}

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