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Issue title: Special Issue on the 30th Italian Conference on Computational Logic: CILC 2015
Guest editors: Marco Maratea, Viviana Mascardi, Davide Ancona and Alberto Pettorossi
Article type: Research Article
Authors: Lisi, Francesca A.; † | Mencar, Corrado
Affiliations: Dipartimento di Informatica, and C.I.L.A. (Centro Interdipartimentale di Logica e Applicazioni), Università degli Studi di Bari “Aldo Moro”, Bari, Italy. {FrancescaAlessandra.Lisi, Corrado.Mencar}@uniba.it
Correspondence: [†] Address for correspondence: Dipartimento di Informatica, and C.I.L.A. (Centro Interdipartimentale di Logica e Applicazioni), Università degli Studi di Bari “Aldo Moro” v. E. Orabona 4, 70125 Bari, Italy.
Note: [*] This work was partially funded by the Università degli Studi di Bari “Aldo Moro” under the IDEA Giovani Ricercatori 2011 grant “Dealing with Vague Knowledge in Ontology Refinement”.
Abstract: We propose a method to extract and integrate fuzzy information granules from a populated OWL ontology. The purpose of this approach is to represent imprecise knowledge within an OWL ontology, as motivated by the fact that the Semantic Web is full of imprecise and uncertain information coming from perceptual data, incomplete data, data with errors, etc. In particular, we focus on Fuzzy Set Theory as a means for representing and processing information granules corresponding to imprecise concepts usually expressed by linguistic terms. The method applies to numerical data properties. The values of a property are first clustered to form a collection of fuzzy sets. Then, for each fuzzy set, the relative σ-count is computed and compared with a number of predefined fuzzy quantifiers, which are therefore used to define new assertions that are added to the original ontology. In this way, the extended ontology provides both a punctual view and a granular view of individuals w.r.t. the selected property. We use a real-world ontology concerning hotels and populated with data of the Italian city of Pisa, to illustrate the method and to test its implementation. We show that it is possible to extract granular properties that can be described in natural language and smoothly integrated in the original ontology by means of annotated assertions.
Keywords: Ontologies, OWL, Granular Computing, Fuzzy Set Theory
DOI: 10.3233/FI-2018-1661
Journal: Fundamenta Informaticae, vol. 159, no. 1-2, pp. 147-174, 2018
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