Integration of Contextual Descriptors in Ontology Alignment for Enrichment of Semantic Correspondence
Abstract
This paper proposes a novel approach to semantic ontology alignment using contextual descriptors. A formalization was developed that enables the integration of essential and contextual descriptors to create a comprehensive knowledge model. The hierarchical structure of the semantic approach and the mathematical apparatus for analyzing potential conflicts between concepts, particularly in the example of "Transparency" and "Privacy" in the context of artificial intelligence, are demonstrated. Experimental studies showed a significant improvement in ontology alignment metrics after the implementation of contextual descriptors, especially in the areas of privacy, responsibility, and freedom & autonomy. The application of contextual descriptors achieved an average overall improvement of approximately 4.36%. The results indicate the effectiveness of the proposed approach for more accurately reflecting the complexity of knowledge and its contextual dependence.
Keywords
Cite
@article{arxiv.2411.19113,
title = {Integration of Contextual Descriptors in Ontology Alignment for Enrichment of Semantic Correspondence},
author = {Eduard Manziuk and Oleksander Barmak and Pavlo Radiuk and Vladislav Kuznetsov and Iurii Krak and Sergiy Yakovlev},
journal= {arXiv preprint arXiv:2411.19113},
year = {2024}
}
Comments
Ontology alignment, contextual descriptors, semantic matching, knowledge representation, essential descriptors, ontology integration, hierarchical structure, semantic heterogeneity, ethical AI