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Guest Talk: Semantic Interactive Ontology Matching: Synergistic Combination of Techniques to Improve the Set of Candidate Correspondences

Dr. Kate Revoredo 

Date/Time: 25.10.2017, 17:00 

Location: D2.2.094 

Abstract 

Ontology Matching is the task of finding a set of entity correspondences between a pair of ontologies, i.e. an alignment. It has been receiving a lot of attention due to its broad applications. Many techniques have been proposed, among which the ones applying interactive strategies. An interactive ontology matching strategy uses expert knowledge towards improving the quality of the final alignment. When these strategies are based on the expert feedback to validate correspondences, it is important to establish criteria for selecting the set of correspondences to be shown to the expert. A bad definition of this set can prevent the algorithm from finding the right alignment or it can delay convergence. On the other way around, techniques that consider the semantics of the entities of the ontology have shown good results. In this work we present techniques which, when used simultaneously, improve the set of candidate correspondences. These techniques are incorporated in an interactive ontology matching approach, called ALINSem. Experiments successfully show the potential of our proposal.

Bio 

Kate Revoredo is an Associated Professor of the Department of Applied Informatics at the Federal University of the State of Rio de Janeiro (UNIRIO), Brazil. She obtained a D.Sc. and a M.Sc. in Computer Science with emphasis in Artificial Intelligence from the Federal University of Rio de Janeiro (COPPE-UFRJ). During her D.Sc. studies in the context of automatic adaptation of probabilistic relational models, she was a visiting researcher at Machine Learning and Natural Language Processing Lab at Albert-Ludwigs-University Freiburg, Germany. Her research focus is mainly on machine learning and data mining, more specifically on algorithms for learning and adapting ontologies and their alignments through data. Moreover, she is also work with process discovery and monitoring through data. She has published in important journals and conference papers, participates in several program committees of journals and conferences, and is a member of the Brazilian Computer Society and the Brazilian Special Commission in Artificial Intelligence.



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