Skip to content
DSML.KZ
Publications

Talk · IEEE International Conference on Smart Information Systems and Technologies · May 13, 2026

Universal Framework for Integrating New Concepts Into Ontologies Across Multiple Domains

Bayangali Abdygalym, Zhanna B. Sadirmekova, Madina Sambetbayeva, Roman Taberkhan

Roman Taberkhan
Open via DOI

Abstract

Ontologies must be regularly expanded through the incorporation of new concepts and relationships due to the ongoing evolution of topic areas. Conventional ontological evolution techniques are time-consuming, prone to error, and limited in scalability because they mostly rely on the manual labor of specialists. This article proposes a universal framework for integrating new concepts into the ontology of various subject areas based on the use of language models. The framework implements a three-step process that includes semantic candidate generation, contextual validation, and formal ontological placement of concepts. Language models are used to analyze textual definitions, calculate semantic similarities, and identify hierarchical relationships between concepts. Experimental evaluation was carried out on medical (SNOMED CT), industrial and educational ontologies. The experimental results demonstrate an increase in the accuracy of concept placement and significant reduction in the amount of expert corrections compared to traditional rule-based approaches. The proposed framework has versatility and can be used to support the evolution of ontologies in various applied fields.

Semantic Web and OntologiesBiomedical Text Mining and OntologiesTopic Modelingontology evolutionconceptual blendinglanguage models

More by Roman Taberkhan