KCE

Key Concept Extraction

KCE defines a groundbreaking approach to identifying the concepts in an ontology, which best summarize what the ontology is about. KCE makes use of a number of criteria, drawn from cognitive science, network topology, and lexical statistics to try and produce the kind of ontology summaries which human experts would come up with. Indeed a formal evaluation of the method has shown an excellent degree of correlation with the choices of the experts. While the generation of automatic methods for ontology summarization is an interesting research area in itself, KCE also provides a basis for novel approaches to a variety of ontology engineering tasks, including ontology matching, automatic classification, ontology modularization, and ontology

evaluation.

Motta, E., Mulholland, P., Peroni, S., d'Aquin, M., Gomez-Perez, J., Mendez, V. and Zablith, F. (2011) A Novel Approach to Visualizing and Navigating Ontologies, International Semantic Web Conference, ISWC 2011, Bonn, Springer-Verlag

Motta, E., Peroni, S., Li, N. and d'Aquin, M. (2010) KC-Viz: A Novel Approach to Visualizing and Navigating Ontologies, Demo at The 17th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2010), Lisbon, Portugal.

Peroni, S., Motta, E. and d'Aquin, M. (2008) Identifying key concepts in an ontology through the integration of cognitive principles with statistical and topological measures, Third Asian Semantic Web Conference, Bangkok, Thailand