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Main Authors: Teymurova, Sevinj, Jiménez-Ruiz, Ernesto, Weyde, Tillman, Chen, Jiaoyan
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2408.06310
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author Teymurova, Sevinj
Jiménez-Ruiz, Ernesto
Weyde, Tillman
Chen, Jiaoyan
author_facet Teymurova, Sevinj
Jiménez-Ruiz, Ernesto
Weyde, Tillman
Chen, Jiaoyan
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2408_06310
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle OWL2Vec4OA: Tailoring Knowledge Graph Embeddings for Ontology Alignment
Teymurova, Sevinj
Jiménez-Ruiz, Ernesto
Weyde, Tillman
Chen, Jiaoyan
Artificial Intelligence
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.
title OWL2Vec4OA: Tailoring Knowledge Graph Embeddings for Ontology Alignment
topic Artificial Intelligence
url https://arxiv.org/abs/2408.06310