Manuel Fiorelli

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In this paper we introduce CODA (Computer-aided Ontology Development Architecture), an Architecture and a Framework for semi-automatic development of ontologies through analysis of heterogeneous information sources. We have been motivated in its design by observing that several fields of research provided interesting contributions towards the objective of(More)
In this paper we briefly describe the ART Lab infrastructure for semantic Big Bata processing. Our most relevant contribution is the definition of an architecture supporting ontology development driven by knowledge acquired from heterogeneous resources, such as documents and web pages. The overall perspective is to propose a gluing architecture driving and(More)
Ontology mediators often demand extensive configuration, or even the adaptation of the input ontologies for remedying unsupported modeling patterns. In this paper we propose MAPLE (MAPping Architecture based on Linguistic Evidences), an architecture and software platform that semi-automatically solves this configuration problem, by reasoning on metadata(More)
In this paper, we introduce Sheet2RDF, a platform for the acquisition and transformation of spreadsheets into RDF datasets. Based on Apache UIMA and CODA, two wider-scoped frameworks respectively aimed at knowledge acquisition from unstructured information and RDF triplification, Sheet2RDF narrows down their capabilities in order to restrict the domain of(More)
We present a practical problem that involves the analysis of a large dataset of heterogeneous documents obtained by crawling the web for information related to web services. This analysis includes information extraction from natural-language (HTML and PDF) and machine-readable (WSDL) documents using NLP and other techniques, classifying documents as well as(More)