OWL2Vec4OA: Tailoring Knowledge Graph Embeddings for Ontology Alignment

TL;DR

This paper introduces OWL2Vec4OA, an extension of OWL2Vec* that incorporates edge confidence to improve ontology alignment, demonstrating promising results in semantic interoperability.

Contribution

It presents a novel method to tailor ontology embeddings for alignment by integrating seed mapping confidence into the embedding process.

Findings

Enhanced embedding quality for ontology alignment

Improved alignment accuracy over baseline methods

Effective incorporation of seed confidence values

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.