Fedelucio Narducci
Postdoctoral Researcher, PhD

University of Bari "Aldo Moro"
Department of Computer Science
Via E.Orabona, 4 - 70126 BARI, Italy

Phone: +39 080 5442298
Fax: +39 080 5443196
e-mail: narducci___AT___di.uniba.it

Research Interests and Activities | Short Curriculum | Tools

Main Research Interests

• Recommender Systems
• Information Filtering
• Machine Learning Techniques for Recommender Systems
• User Modeling and Profiling
• Linked Open Data
• e-Government
• e-Health

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Short CV

• AUGUST 2014 - I got a post-doc at University of Bari under the supervision of Dr. Marco de Gemmis. My research was focused on techniques of information filtering for diversifying recommendations of multimedia content.
• APRIL 2012 - July 2014 I got a post-doc at University of Milano Bicocca under the supervision of Prof. Carlo Batini. My research was focused on techniques for the intelligent access to multilingual e-gov service.
• JUNE 2012 - I received a Ph.D. in Computer Science from University of Bari under the supervision of Dr. Pasquale Lops. I discussed a thesis titled: ″`Knowledge-enriched Representations for Content-based Recommender Systems″
• APRIL 2011 - I joined the Human Interaction and Experiences research group of the Philips Research center in Eindhoven (The Netherlands) for a three months fellowship under the supervision of Ing. Mauro Barbieri.
• JANUARY 2009 - I started the Ph.D. Course in Computer Science at Department of Computer Science, University of Bari. My supervisor is PhD Pasquale Lops.
• APRIL 2008 - I received a Master's Degree with full marks and honors in Computer Science from University of Bari. I discussed a thesis titled: ″Parameters estimating and feature weighing in a bayesian classifier: applying of Poisson's distribution and risk assessment ″.

Summer Schools

• SSSC 2010 - IEEE 2010 Summer School on Semantic Computing - Berkeley (CA, United States), July 25-31, 2010
• ACAI 2009 - Advanced Course in Artificial Intelligence '09 Intelligent Decision Support Systems (theory, algorithms, and applications) - Belfast (Northern Ireland), August 23-29, 2009

Awards

• 1st Place - Top-N recommendation from binary user feedback - ESWC-14 Challenge Linked Open Data-enabled Recommender Systems: P. Basile, C. Musto, M. De Gemmis, P. Lops, F. Narducci and G. Semeraro. Aggregation strategies for Linked Open Data-enabled Recommender Systems, 2014.
• Most Inspiring Contribution Award - 21st Conference on User Modeling, Adaptation and Personalization. F. Narducci, C. Musto, G. Semeraro, P. Lops, M. De Gemmis. Leveraging Encyclopedic Knowledge for Transparent and Serendipitous, 2013 User Proles.
• SSSC 2010 - IEEE 2010 Summer School on Semantic Computing - Berkeley (CA, United States), July 25-31, 2010 - 1st prize award for the contribution in the Student Project works organized within the Summer School. The work focused on the development of GeoMusic a tool for the suggestion of personalized and geo-localized music playlists.

Tutoring

• 2009/10 - Corso di Programmazione, CdL in Informatica e Tecnologie per la produzione del software.
• 2009/10 - Corso di Linguaggi di Programmazione + Lab. - CdL in Informatica - (Link) - (Join Facebook Group)

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Associations

• AI*IA (Associazione Italiana per l'Intelligenza Artificiale);

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Tools

• FIRSt. Folksonomy-based ITem Recommender is a content-based item recommending on the basis of ratings given by users. It use a Naïve Bayes text classification to assign a score (level of interest) to items according to the user preferences. The user profile containing the probabilistic model (words/synsets + probabilities) of user preferences.
• STAR. Social Tag Recommender is a content-based tag recommender. It suggests tags for Bibsonomy bookmarks and BibTeXs entries exploiting tags used by the community to annotate similar resources. STaR participates at the ECML/PKDD Discovery Challenge 2009.
• MovieRecSysBot. Conversational Movie Recommender implemented as Telegram chatbot