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Erschienen in:
2014 | OriginalPaper | Buchkapitel
A Tool for Theme Identification in RDF Graphs
verfasst von : Hanane Ouksili, Zoubida Kedad, Stéphane Lopes
Erschienen in: Natural Language Processing and Information Systems
Verlag: Springer International Publishing
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An increasing number of RDF datasets is published on the Web. A user willing to use these datasets will first have to explore them in order to determine which information is relevant for his own needs. To facilitate this exploration, we present a system which provides a thematic view of a given RDF dataset, making it easier to target the relevant resources and properties. Our system combines a density-based graph clustering algorithm with semantic clustering criteria in order to identify clusters, each one corresponding to a theme. In this paper, we will give an overview of our approach for theme identification and we will present our system along with a scenario illustrating its main features.