AL-QuIn: An Onto-Relational Learning System for Semantic Web Mining

Francesca A. Lisi
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Francesca A. Lisi: Università degli Studi di Bari “Aldo Moro”, Italy

International Journal on Semantic Web and Information Systems (IJSWIS), 2011, vol. 7, issue 3, 1-22

Abstract: Onto-Relational Learning is an extension of Relational Learning aimed at accounting for ontologies in a clear, well-founded and elegant manner. The system -QuIn supports a variant of the frequent pattern discovery task by following the Onto-Relational Learning approach. It takes taxonomic ontologies into account during the discovery process and produces descriptions of a given relational database at multiple granularity levels. The functionalities of the system are illustrated by means of examples taken from a Semantic Web Mining case study concerning the analysis of relational data extracted from the on-line CIA World Fact Book.

Date: 2011
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