Claudia d’Amato

Claudia d’Amato graduated in Computer Science at the University of Bari on March 2003 with full marks and honors. After almost one year in a software company, she started her research activity in January 2004 winning a grant from the University of Bari for PhD students in Computer Science. She completed her PhD studies in January 2007 and defended the thesis “Similarity-based Learning Methods for the Semantic Web” on May 2007 receiving a full marks evaluation and also a nomination from the Italian Commission for the AI*IA award 2007 as one of the Best Italian PhD theses in Artificial Intelligence. Since April 2004 she is a research assistant at the University of Bari - Computer Science Department and she is investigating on the analysis and the application of Machine Learning (ML) methods to the Semantic Web (SW) domain. The results of the research activities have been applied in several regional, national and European research projects. Claudia d’Amato also collaborated/collaborates with international universities and research organizations. During January-June 2006, February-May 2007, February-April 2008, Claudia d’Amato was visiting researcher at the University of Koblenz- Landau (Germany). In June 2011, Claudia d’Amato was invited researcher at the University of Poznan (Poland). In March-April 2012 was invited researcher at the Fondazione Bruno Kessler, Trento (Italy).

The research activity of Claudia d’Amato has been disseminated in 13 journal articles, 8 book chapters, 37 articles in international collections, 18 articles in international workshop collections and 12 articles in national conferences and workshops collections. Claudia d’Amato has been also editor of 12 books/collections and 2 journal special issues. She has served the editorial board of international journals in the field such as the Semantic Web Journal and she has also served the program committee of more than 50 international conferences such as the International and the European Semantic Web Conference(ISWC, ESWC), the American, European and the International Conference on Artificial Intelligence (AAAI, ECAI, IJCAI), the International and the European Conference on ML (ICML, ECML). In 2008, Claudia d’Amato served as vice-Chair for ISWC and in 2012 as workshop and tutorial chair. She also served as ML track chair at ESWC 2012. Claudia d’Amato has also been organizer of the International Uncertainty Reasoning Workshop at ISWC (URSW 2011-10-09-08,-07) and the International Workshop on Inductive Reasoning and ML on the Semantic Web at ESWC (IRMLeS 2011,-10.-09). Her research activity also received the following credits: Best Paper at ACM SAC’10 - SWA Track for the paper “Recovering Uncertain Mappings through Structural Validation and Aggregation with the MoTo System” and Best best student paper at SEBD07 for the paper “Constraint Hardness for Modelling, Matching and Ranking Semantic Web services”. She has been also invited speaker at various international universities, seminars and conferences over the years.

Publications

Collaboration and the Semantic Web: Social Networks, Knowledge Networks, and Knowledge Resources
Stefan Brüggemann, Claudia d’Amato. © 2012. 387 pages.
Collaborative working has been increasingly viewed as a good practice for organizations to achieve efficiency. Organizations that work well in collaboration may have access to...
Inductive Classification of Semantically Annotated Resources through Reduced Coulomb Energy Networks
Nicola Fanizzi, Claudia d’Amato, Floriana Esposito. © 2011. 21 pages.
The tasks of resource classification and retrieval from knowledge bases in the Semantic Web are the basis for a lot of important applications. In order to overcome the...
Evolutionary Conceptual Clustering Based on Induced Pseudo-Metrics
Nicola Fanizzi, Claudia d’Amato, Floriana Esposito. © 2010. 24 pages.
We present a method based on clustering techniques to detect possible/probable novel concepts or concept drift in a Description Logics knowledge base. The method exploits a...
Inductive Classification of Semantically Annotated Resources through Reduced Coulomb Energy Networks
Nicola Fanizzi, Claudia d’Amato, Floriana Esposito. © 2009. 20 pages.
The tasks of resource classification and retrieval from knowledge bases in the Semantic Web are the basis for a lot of important applications. In order to overcome the...
Evolutionary Conceptual Clustering Based on Induced Pseudo-Metrics
Nicola Fanizzi, Claudia d’Amato, Floriana Esposito. © 2008. 24 pages.
We present a method based on clustering techniques to detect possible/probable novel concepts or concept drift in a Description Logics knowledge base. The method exploits a...