A Clustering Based Approach for Type Discovery in RDF Data Sources
Résumé
RDF(S)/OWL data sources are not organized according to a predefined schema, as they are structureless by nature. This lack of schema limits their use to express queries or to understand their content. Our work is a contribution towards the inference of the structure of RDF(S)/OWL data sources. We present an approach relying on density-based clustering to discover the types describing the entities of possibly incomplete and noisy data sets.