Ontology Matching

Ontology matching aims to identify correspondences between entities across different ontologies, facilitating data interoperability and knowledge sharing. Current research emphasizes leveraging advanced techniques like graph representation learning, large language models (LLMs), and active learning to improve matching accuracy and efficiency, particularly for complex or weakly informative ontologies. These advancements are driving progress in diverse fields, including bioinformatics and the semantic web, by enabling seamless integration of heterogeneous datasets and knowledge bases. The development of robust benchmark datasets and evaluation frameworks is also a key focus, ensuring the reliable assessment of novel ontology matching approaches.