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BIBTEX RIS

ABSTAT: Linked Data Summaries with ABstraction and STATistics

2015; Springer Science+Business Media; Linguagem: Inglês

10.1007/978-3-319-25639-9_25

ISSN

1611-3349

Autores

Matteo Palmonari, Anisa Rula, Riccardo Porrini, Andrea Maurino, Blerina Spahiu, Vincenzo Ferme,

Tópico(s)

Natural Language Processing Techniques

Resumo

While much work has focused on continuously publishing Linked Open Data, little work considers how to help consumers to better understand existing datasets. ABSTAT framework aims at providing a better understanding of big and complex datasets by extracting summaries of linked data sets based on an ontology-driven data abstraction model. Our ABSTAT framework takes as input a data set and an ontology and returns an ontology-driven data summary as output. The summary is exported into RDF and then made accessible through a SPARQL endpoint and a web interface to support the navigation.

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