SWAP - Semantic Web Access and Personalization Research Group

Cataldo Musto
Assistant Professor (Ricercatore a Tempo Determinato), Ph.D.

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: cataldo.musto___AT___uniba.it







Research Interests | Short Curriculum | Publications | Tools | Links





Main Research Interests

  • Recommender Systems
  • Information Filtering
  • Distributional Semantics
  • Social Media and Linked Data for User Modeling
  • Recommender Systems and Big Data
  • Tag Recommendation



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Last Update: September 1, 2014

Short CV

  • JUNE 2012 - I received a Ph.D. in Computer Science from University of Bari. I discussed a thesis titled: ″Enhanced Vector Space Models 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 internship 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, under the supervision of Prof. Giovanni Semeraro. The topic of my thesis concerns the study of innovative recommendation techniques and preference elicitations approaches into the Semantic and Social Web context.
  • APRIL 2008 - I received a Laurea Degree with full marks and honors in Computer Science from University of Bari. I discussed a thesis titled: ″Extending a Content-Based recommender system through semantic folskonomies″.

Ph.D.

Awards

  • UMAP 2012 I received a $1000 student grant to attend the conference and present a paper at the Industrial track.
  • SSSC 2010 - IEEE 2010 Summer School on Semantic Computing - Berkeley (CA, United States), July 25-31, 2010 - 1st prize award (link) 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 Progettazione di Basi di Dati, CdL in Informatica e Tecnologie per la produzione del software - (Link)
  • 2009/10 - Corso di Linguaggi di Programmazione + Lab. - CdL in Informatica - (Link)

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



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Associations

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



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Publications

International Journals

  • G.Semeraro, P.Lops, M. de Gemmis, C. Musto, and F. Narducci. A folksonomy-based recommender system for personalized access to digital artworks. Journal on Computing and Cultural Heritage (JOCCH), 5:11-34, 2012. (download PDF)
  • P. Lops, M. de Gemmis, G. Semeraro, C. Musto, and F. Narducci. Content-based and collaborative techniques for tag recommendation: an empirical evaluation. Journal of Intelligent Information Systems, pages 1-21, 2012. ISSN 0925-9902.

Chapters in International Volumes

  • M. de Gemmis, L. Iaquinta, P. Lops, C. Musto, F. Narducci, G. Semeraro. Learning Preference Models in Recommender Systems. In: Preference Learning. Edited by: In Eyke Hxllermeier and Johannes Furnkranz. Springer, Berlin (Germany), 2009. (download PDF)
  • P. Lops, M. de Gemmis, G. Semeraro, C. Musto, and F. Narducci, and M. Bux. Semantic Content-based Recommender System Integrating Folksonomies for Personalized Access. In: G. Castellano, L. Jain AND A. M. Fanelli. Web Personalization in Intelligent Environments. 27-47 vol. SCI 229. ISBN: 978-3-642-02793-2. Springer, Berlin (Germany) (download PDF)

Conference Papers

  • C. Musto, G. Semeraro, P. Lops, and M. de Gemmis: Combining Distributional Semantics and Entity Linking for Context-Aware Content-Based Recommendation. In V. Dimitrova, T. Kuflik, D. Chin, F. Ricci, P. Dolog, G.J. Houben (Eds.): User Modeling, Adaptation, and Personalization - 22nd International Conference, UMAP 2014: pages 381-392. ISBN 978-3-319-08785-6, 2014 (download PDF)
  • C. Musto, G. Semeraro, P. Lops, and M. de Gemmis. Contextual evsm: A content-based context-aware recommendation framework based on distributional semantics. In C. Huemer and P. Lops, editors, EC-Web, volume 152 of Lecture Notes in Business Information Processing, pages 125-136. Springer, 2013. ISBN 978-3-642-39877-3. (download PDF)
  • F. Narducci, C. Musto, G. Semeraro, P. Lops, and M. de Gemmis. Exploiting big data for enhanced representations in content-based recommender systems. In C. Huemer and P. Lops, editors, EC-Web, volume 152 of Lecture Notes in Business Information Processing, pages 182-193. Springer, 2013. ISBN 978-3-642-39877-3. (download PDF)
  • F. Narducci, C. Musto, G. Semeraro, P. Lops, and M. de Gemmis. Leveraging encyclopedic knowledge for transparent and serendipitous user pro les. In S. Carberry, S. Weibelzahl, A. Micarelli, and G. Semeraro, editors, UMAP, volume 7899 of Lecture Notes in Computer Science, pages 350-352. Springer, 2013. ISBN 978-3-642-38843-9. (download PDF)
  • C. Musto, F. Narducci, P. Lops, G. Semeraro, M. de Gemmis, M. Barbieri, J. H. M. Korst, V. Pronk, and R. Clout. Enhanced semantic tv-show representation for personalized electronic program guides. In J. Masthoff, B. Mobasher, M. C. Desmarais, and R. Nkambou, editors, UMAP, volume 7379 of Lecture Notes in Computer Science, pages 188-199. Springer, 2012. ISBN 978-3-642-31453-7. (download PDF)
  • C. Musto, G. Semeraro, P. Lops, M. de Gemmis, and F. Narducci. Leveraging social media sources to generate personalized music playlists. In C. Huemer and P. Lops, editors, EC-Web, volume 123 of Lecture Notes in Business Information Processing, pages 112-123. Springer, 2012. ISBN 978-3-642-32272-3. (download PDF)
  • P. Lops, M. de Gemmis, G. Semeraro, F. Narducci, and C. Musto. Leveraging the linkedin social network data for extracting content-based user profi les. In B. Mobasher, R. D. Burke, D. Jannach, and G. Adomavicius, editors, RecSys, pages 293-296. ACM, 2011. ISBN 978-1-4503-0683-6 (download PDF)
  • C. Musto, F. Narducci, P. Basile, P. Lops, M. de Gemmis, and G. Semeraro. Cross-language information ltering: Word sense disambiguation vs. distributional models. In R. Pirrone and F. Sorbello, editors, AI*IA, volume 6934 of Lecture Notes in Computer Science, pages 250-261. Springer, 2011. ISBN 978-3-642-23953-3 (download PDF)
  • C. Musto, G. Semeraro, P. Lops, and M. de Gemmis. Random indexing and negative user preferences for enhancing content-based recommender systems. In C. Huemer and T. Setzer, editors, EC-Web, volume 85 of Lecture Notes in Business Information Processing, pages 270-281. Springer, 2011. ISBN 978-3-642-23013-4.(download PDF)
  • P. Lops, C. Musto, F. Narducci, M. de Gemmis, P. Basile, and G. Semeraro. Cross-language personalization through a semantic content-based recommender system. In D. Dicheva and D. Dochev, editors, AIMSA, volume 6304 of Lecture Notes in Computer Science, pages 52-60. Springer, 2010. ISBN 978-3-642-15430-0. (download PDF)
  • C. Musto. Enhanced vector space models for content-based recommender systems. In Proceedings of the fourth ACM conference on Recommender systems, RecSys'10, pages 361-364. ACM, New York, NY, USA, 2010. ISBN 978-1-60558-906-0. (download PDF)
  • C. Musto, F. Narducci, P. Lops, and M. de Gemmis. Combining collaborative and content-based techniques for tag recommendation. In F. Buccafurri and G. Semeraro, editors, EC-Web, volume 61 of Lecture Notes in Business Information Processing, pages 13-23. Springer, 2010. ISBN 978-3-642-15207-8 (download PDF)
  • C.Musto, F. Narducci, P. Lops, M. de Gemmis, G. Semeraro. Exploiting content-based recommender systems and digital libraries for cultural heritage personalization In: Proceedings of the 6th Italian Research Conference on Digital Libraries - IRCDL 2010, Padua, Italy, January 28-29, 2010 (download PDF)
  • C. Musto, F. Narducci, P. Lops, M. de Gemmis, and G. Semeraro. Content-based Personalization Services Integrating Folksonomies. In E-Commerce and Web Technologies, 10th International Conference, EC-Web 2009, Linz, Austria, September 1-4, 2009, volume 5692 of Lecture Notes in Computer Science. 217-228, BERLIN: Springer, 2009, ISBN 978-3-642-03963-8 (download PDF)
  • P. Basile, M. de Gemmis, L. Iaquinta, P. Lops, C. Musto, F. Narducci, G. Semeraro. SpIteR : a Module for Recommending Dynamic Personalized Museum Tours In Proceedings of the 2009 IEEE/WIC/ACM Intíl Joint Conf. on Web Intelligence & Intelligent Agent Technology (WI-IAT 2009) LOS ALAMITOS, CA Ė USA: IEEE Computer Society Press. (download PDF)
  • P. Lops, M. de Gemmis, G. Semeraro, P. Gissi, C. Musto, F. Narducci. Content-based Filtering with Tags : the FIRSt System. In Proceedings of the 9th International Conference on Intelligent Systems Design and Applications (ISDA 2009). (download PDF)

National and International Workshops

  • C. Musto, F. Narducci, P. Basile, P. Lops, M. de Gemmis, and G. Semeraro. Comparing word sense disambiguation and distributional models for cross-language information filtering. In IIR, pages 117-120. 2012. (download PDF)
  • C. Musto, F. Narducci, P. Lops, G. Semeraro, M. de Gemmis, M. Barbieri, J. H. M. Korst, V. Pronk, and R. Clout. Tv-show retrieval and classi cation. In IIR, pages 179-182. 2012. (download PDF)
  • C. Musto, P. Lops, M. de Gemmis, and G. Semeraro. Random indexing for

content-based recommender systems. In M. Melucci, S. Mizzaro, and G. Pasi, editors, IIR, volume 704 of CEUR Workshop Proceedings. CEUR-WS.org, 2011.

  • C. Musto. Boosting Content-based Recommender Systems through Advanced Vector Space Models. In Abstract Booklet of the 1st AI*IA Doctoral Consortium, pages 87-91. December 1-3 2010. (download PDF)
  • P. Lops, 'C. Musto', F. Narducci, M. de Gemmis, P. Basile, and G. Semeraro. Learning semantic content-based pro les for cross-language personalization. In Proceedings of the Workshop on Personalized Multimedia Hypertext Retrieval (PMHR11). June 6 2011. (download PDF)
  • P. Lops, 'C. Musto', F. Narducci, M. de Gemmis, P. Basile, and G. Semeraro. MARS:a multilanguage recommender system. In Proceedings of the 1st International Workshop on Information Heterogeneity and Fusion in Recommender Systems (HetRec 2010). September 26 2010.
  • C. Musto, F. Narducci, M. De Gemmis, P. Lops, G. Semeraro, An IR-based approach for Tag Recommendation. Proceedings of the First Italian Information Retrieval Workshop (IIR-2010), Padua, Italy, January 27-28, 2010. Edited by: Massimo Melucci, Stefano Mizzaro, Gabriella Pasi. CEUR-WS.org, Volume 560 of CEUR Workshop Proceedings
  • M. de Gemmis, L. Iaquinta, P. Lops, C. Musto, F. Narducci, and G. Semeraro. Preference Learning in Recommender Systems. In Proceedings of the ECML/PKDD 2009 Workshop on Preference Learning, pages 41-55. September 11 2009.
  • C. Musto, F. Narducci, M. de Gemmis, P. Lops, and G. Semeraro. A

Tag Recommender System Exploiting User and Community Behavior. In D. Jannach, W. Geyer, J. Freyne, S. S. Anand, C. Dugan, B. Mobasher, and A. Kobsa, editors, Proceedings of the ACM RecSys 2009 Workshop on Recommender Systems & The Social Web, volume 532 of CEUR Workshop Proceedings. NEW YORK, October 25 2009. ISSN 1613-0073.

  • C. Musto, F. Narducci, M. de Gemmis, P. Lops, G. Semeraro. STaR : a Social Tag Recommender System. In Proceedings of the ECML/PKDD 2009 Discovery Challenge Workshop. CEUR-WS.org, Volume 497 of CEUR Workshop Proceedings, ISSN 1613-0073.
  • P. Basile, F. Calefato, M. de Gemmis, P. Lops, G. Semeraro, M. Bux, C. Musto, and F. Narducci. Augmenting a Content-based Recommender System with Tags for Cultural Heritage Personalization. In L. Aroyo, T. Kuflik, O. Stock, and M. Zancanaro, editors, Proceedings of the Workshop on Personalized Access to Cultural Heritage (PATCH 2008) at the 5th International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems (AH 2008), Hannover, Germany, pages 25-34. July 29, 2008.
  • P. Basile, F. Calefato, M. de Gemmis, P. Lops, G. Semeraro, M. Bux, C. Musto, and F. Narducci. Cultural Heritage Personalization using a Content-based Recommender System and Folksonomies. In G. Armano, M. Schaerf, and G. Semeraro, editors, Proceedings of the AI*IA 2008 Workshop on Artificial Intelligence for the Cultural Heritage, Cagliari, Italy, pages 46-54. September 11, 2008.
  • P. Basile, M. de Gemmis, P. Lops, G. Semeraro, M. Bux, C. Musto, and F. Narducci. First: a content-based recommender system integrating tags for cultural heritage personalization. In Proceedings of the 4th International Conference on Automated Solutions for Cross Media Content and Multi-channel Distribution (AXMEDIS 2008) - Workshop on Cultural heritage and Artificial Intelligence, Florence, Italy, 17-19 November, 2008.



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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 NaÔve 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.



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Links