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Issue title: Artificial Intelligence in the Catalan Association for AI
Article type: Research Article
Authors: Moreno, Antonio; | Valls, Aïda | Martínez, Sergio | Vicient, Carlos | Marín, Lucas | Mata, Ferran
Affiliations: Departament d'Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, Tarragona, Spain
Note: [] Corresponding author: Antonio Moreno, Departament d'Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, Avda. Països Catalans 26, 43007 Tarragona, Spain. Tel.: +34 977 559681; Fax: +34 977 559710; E-mail: antonio.moreno@urv.cat
Abstract: Intelligent data analysis methods usually require as input a matrix, in which each row is an object to be analysed and each column is an attribute. In most cases it is assumed that attributes are Boolean, categorical or numerical. With the advent of semantic domain information in the form of ontologies, it is now common to find also semantic attributes, which may take as value a list of concepts. This paper proposes a new ontology-based procedure to compute the similarity between lists of semantic values, which may be used to compare objects. This measure is employed in an enhanced version of the k-means clustering method. The usefulness of the obtained classes has been tested in the context of a Web-based personalised recommender of Tourist destinations.
Keywords: Semantic similarity, ontologies, clustering
DOI: 10.3233/AIC-140612
Journal: AI Communications, vol. 28, no. 1, pp. 127-142, 2015
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