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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


Motta, Enrico, Mulholland, Paul, Peroni, Silvio, d'Aquin, Mathieu, Gomez-Perez, Jose Manuel, Mendez, Victor, Zablith, Fouad, A novel approach to visualizing and navigating ontologies

Motta, Enrico, Peroni, Silvio, Li, Ning, d'Aquin, Mathieu, KC-Viz: a novel approach to visualizing and nNavigating ontologies

Peroni, Silvio, Motta, Enrico, d'Aquin, Mathieu, Identifying key concepts in an ontology, through the integration of cognitive principles with statistical and topological measures


Silvio Peroni Mathieu dAquin Enrico Motta


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