Ontology Learning

Ontology learning studies how to build and refine structured representations of concepts, relationships, and logical constraints so that knowledge can be searched, integrated, and reasoned over. Approaches include description-logic concept learning and active learning, formal concept analysis, embeddings and clustering, and LLM-based extraction or generation grounded in existing vocabularies and retrieval. Evaluation spans ontology completion, term typing, taxonomy discovery, alignment, and competency-question benchmarks, with attention to structural and logical correctness as well as vocabulary coverage. Language models can speed up drafting and expansion, but reliably capturing complex relations, producing consistent axioms, and transferring across domains still often requires formal validation and expert review.