Abstract
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 on measurements that are real distances: i.e. that satisfy all the properties of a distance. This paper presents one isa -distance measurement that may be applied to taxonomies. This distance, combined with a distance based on relations other than isa, may be a step towards a real semantic distance for ontologies. After presenting the purpose of this work and the position of our approach within the literature, we formally detail our isa-distance. It is extended to other relations and used to obtain a MDS projection of a musical ontology in an industrial project. The utility of such a distance in visualization, navigation, information research and ontology engineering is underlined.
An erratum to this chapter can be found at http://dx.doi.org/10.1007/11915072_109.
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Ranwez, S., Ranwez, V., Villerd, J., Crampes, M. (2006). Ontological Distance Measures for Information Visualisation on Conceptual Maps. In: Meersman, R., Tari, Z., Herrero, P. (eds) On the Move to Meaningful Internet Systems 2006: OTM 2006 Workshops. OTM 2006. Lecture Notes in Computer Science, vol 4278. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11915072_7
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DOI: https://doi.org/10.1007/11915072_7
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