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Article type: Other
Authors: Batet, Montserrat
Affiliations: Department of Computer Science and Mathematics, Universitat Rovira i Virgili, Av. Paisos Catalans 26, 43007 Tarragona, Spain. E-mail: [email protected]
Abstract: This thesis presents novel measures to estimate the degree of semantic similarity between words using one or more knowledge sources. Several evaluations show that they improve the accuracy of related works. These measures have been applied to clustering to compute the similarity/distance between individuals described by textual attributes. Clustering results show that a proper interpretation of textual data at a semantic level improves the quality of the clusters and ease their interpretation.
Keywords: Semantic similarity, information content, ontologies, clustering
DOI: 10.3233/AIC-2011-0501
Journal: AI Communications, vol. 24, no. 3, pp. 291-292, 2011
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