Finding the right semantic distance to be used for information research, classification or text clustering using Natural Language Processing is a problem studied in several domains of computer science. We focus here on measurements that are real distances: i.e. that satisfy all the properties of a distance.
This distance, combined with a distance based on relations other than ISA, may be a step towards a real semantic distance for ontologies.

This work has been published…
Ontological ISA-Distance Measure for Information Visualisation on Conceptual Maps

    Sylvie Ranwez, Vincent Ranwez, Jean Villerd, Michel Crampes.
In On the Move to Meaningful Internet Systems 2006: OTM 2006 Workshops, Lecture Notes in Computer Science, publisher: Springer Berlin / Heidelberg, Volume 4278/2006, ISBN 978-3-540-48273-4, pp.1050-1061, 2006.

Visual support of the presentation available here.
This measure has been integrated in the SML library.