Interactive Ontology Matching with Cost-Efficient Learning

arXiv:2404.07663v1 Announce Type: cross
Abstract: The creation of high-quality ontologies is crucial for data integration and knowledge-based reasoning, specifically in the context of the rising data economy. However, automatic ontology matchers are often bound to the heuristics they are based on, leaving many matches unidentified. Interactive ontology matching systems involving human experts have been introduced, but they do not solve the fundamental issue of flexibly finding additional matches outside the scope of the implemented heuristics, even though this is highly …

abstract arxiv context cost cs.ai cs.db cs.lg data data integration economy experts heuristics however human integration interactive knowledge ontologies ontology quality reasoning systems type unidentified