Presenters

Pierpaolo Basile is Assistant Professor at the Department of Computer Science, University basile.jpgof Bari Aldo Moro, Italy. He received the Ph.D. in Computer Science from the University of Bari in 2009 with a dissertation on “Word Sense Disambiguation for Intelligent Information Access”. His research interests include natural language processing, machine learning, information retrieval and recommender systems.

He is principal investigator of the project “Multilingual Entity Linking” funded by the regional programme Future In Research.

He has published over 90 papers and served as reviewer or co-reviewer in the Program Committee of several conferences in the area as ESWC, ISWC, CIKM and WWW.

Previous training and speaking experience:

  • He was/is teacher of the following courses at the Department of Computer Science, University of Bari Aldo Moro: “Gestione della Conoscenza d’Impresa” (Knowledge Management), “Accesso Intelligente all’Informazione – modulo B” (Intelligent Information Access – module B) and “Metodi per il Ritrovamento dell’Informazione” (Information Retrieval).
  • He gave the following seminars: “Linked Open Data-enabled Strategies for Top-N Recommendations” – Master degree in Information Technology and Electrical Engineering, University of Naples Federico II; “Information Access with Apache Lucene” – F5 Hit Refresh Open Innovation Camp on Natural Language Processing e Media Screening; “Multilingual Lexical Substitution” – Master degree in Technical Scientific Translation, University of Bari Aldo Moro; “Open Source for Intelligent Information Access” – Open Source conference, Politecnico di Bari.

Personal web site:http://www.di.uniba.it/~basilepp/

Google Scholar profile: https://scholar.google.it/citations?user=dNznumkAAAAJ

 

Tommaso Di Noia is Associate Professor at the Department of Electrical & Information Engineering, Polytdntechnic University of Bari, Italy. Currently, his main research topics deal with Linked Open Data and how to leverage the knowledge encoded in Big Data datasets in order to develop content-based/collaborative/context-aware recommendation engines (recommender systems). Strongly related to this latter research topic is the analysis and modeling of User Profiles in Information Retrieval scenarios. As for Linked Open Data, he is interested in the whole process of production, publication, maintenance and exploitation of the ultimate technological solutions for Open Data.

He has published almost 200 papers and served as reviewer or co-reviewer in the Program Committee of several conferences in the area as RecSys, ESWC, ISWC.

Previous training and speaking experience:

  • Tutorial “Recommender Systems meet Linked Open Data” – at 16th International Conference on Web Engineering (ICWE 2016), Lugano, Switzerland.
  • Lecture “Recommender Systems and Linked Open Data” – at the 11th Reasoning Web Summer School, Berlin, Germany.

Personal web site: http://sisinflab.poliba.it/dinoia 

Google Scholar profile: https://scholar.google.it/citations?user=mPGG34oAAAAJ 

 

03fbe09.jpgCataldo Musto is Assistant Professor at the Department of Computer Science, University of Bari Aldo Moro, Italy. He completed his Ph.D. in 2012 with a dissertation on “Enhanced Vector Space Models for Content-based Recommender Systems”. His research focuses on the adoption of machine learning and natural language processing techniques for semantic content representation in recommender system, user modeling, and intelligent adaptive platforms. He was an invited speaker at the workshop on Semantic Adaptive and Social Web (SASWeb) at UMAP 2012 and at the first workshop on Financial Recommender Systems (FINREC 2015). He has published over 50 papers and served as reviewer or co-reviewer in the Program Committee of several conferences in the area as ACM Recommender Systems, ECIR, UMAP and WWW.

Previous training and speaking experience:

  • Tutorial “Semantics-aware Techniques for Social Media Analysis, User Modeling and Recommender Systems” – at UMAP 2016, 24th Conference on User Modeling, Adaptation and Personalization, Halifax, Canada, July 15, 2016.
  • Meaning is its use: towards the use of distributional semantics for content-based recommender systems, at the International Workshop on Semantic Adaptive Social Web, in conjunction with the Conference on User Modeling, Adaptation and Personalization, UMAP 2012, Montreal, Canada, July 16-20, 2012.
  • Case-based Recommender Systems for Personalized Finance Advisory at the First International Workshop on Personalization & Recommender Systems in Financial Services, FINREC 2016, Graz, Austria, April 16, 2015.

Personal web site: http://www.di.uniba.it/~swap/musto

Google Scholar profile: https://scholar.google.com/citations?user=pauGgdYAAAAJ&hl=it

 

Paolo Tomeo is a Ph.D. candidate in Computer Science Engineering at the Department of downloadElectrical & Information Engineering, Polytechnic University of Bari, Italy. His research interests lie in Recommender Systems and Linked Data fields, with emphasis on Recommendation Diversity, Hybrid Recommendation Algorithms, and Cold-Start Problem.

Personal web site: http://sisinflab.poliba.it/tomeo 

Google Scholar profile: https://scholar.google.it/citations?user=_wzWIM8AAAAJ 

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