Équipe OAK, LRI/INRIA Paris Saclay
Friday 29th January 2016, 14h00
Amphithéatre F107, Inria Grenoble Rhône-Alpes, Montbonnot
Ontologies play a key role in the development of the Semantic Web and are being used in many diverse application domains such as biomedicine and energy industry. An application domain may have been modeled according to different points of view and purposes. This situation usually leads to the development of different ontologies that intuitively overlap, but that use different naming and modeling conventions. In order to enable interoperability between ontology-based systems, ontology matching techniques have been proposed. These techniques, however, rely on lexical and structural heuristics, and the integration of the input ontologies and the mappings may lead to many undesired logical consequences, causing a diminishment of the usefulness of the mappings. We present a multi-strategy approach to detect and correct violations of the so-called conservativity principle, where novel subsumption entailments between named concepts in one of the input ontologies are considered as unwanted. The multi-strategy approach combines graph-theory, logic programming and the use of light-weight logical fragments, in order to achieve scalability in repair computation, even for large biomedical ontologies.
Alessandro Solimando received his BSc, MSc and PhD from the University of Genova, where he defended his thesis on change management for the traditional and Semantic Web, under the supervision of Prof. Giovanna Guerrini and Dr. Ernesto Jimenez-Ruiz. He has been an intern at Inria-Saclay and Universit XI Paris-Sud in 2011 working on optimization for XQuery Update query processing, he has also been a visiting student at University Roma "La Sapienza", and the University of Oxford, working on approximation for Ontology-Based Data Access (OBDA) systems and Ontology-to-ontology Alignment Debugging. In October 2015 he joined Inria-Saclay as a PostDoc fellow. His current research interests are at the intersection of data management and knowledge representation fields, spanning from technologies related to the Semantic Web to distributed data processing, from query optimization to efficient data storage and querying.