Ontology Alignment

Ontology alignment aims to identify correspondences between entities across different ontologies, enabling semantic interoperability and knowledge integration. Current research emphasizes leveraging machine learning, particularly graph neural networks and large language models (LLMs), to improve alignment accuracy, especially for complex relationships beyond simple 1-to-1 mappings. This work is driven by the increasing number of ontologies and the need for automated methods to handle their heterogeneity, impacting diverse fields like bioinformatics and the Semantic Web through improved data integration and knowledge discovery. Furthermore, research explores incorporating user interaction to enhance alignment quality and address limitations of fully automated approaches.