SWAP - Semantic Web Access and Personalization Research Group - CataldoMusto

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Phone: +39 080 5442298
Fax: +39 080 5443196

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Phone: +39 080 5442497

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Web Profiles

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Web Profiles

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Research Interests | Short Curriculum | Publications | Tools | Links

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Research Interests | Short Curriculum | Links | Teaching

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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 proles. 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 profiles. 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 Int�l Joint Conf. on Web Intelligence & Intelligent Agent Technology (WI-IAT 2009) LOS ALAMITOS, CA � 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 classication. 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 proles 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 Na�ve 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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Holistic User Modeling

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Social Media and Linked Data for User Modeling
Recommender Systems and Big Data
Tag Recommendation

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Linked Open Data
Social Media for User Modeling

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JANUARY 2016 - I'm Assistant Professor (Ricercatore a tempo Determinato) at University of Bari. In my research project I will investigate techniques for Semantic Holistic User Modeling.

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JANUARY 2016 - I'm Assistant Professor (Ricercatore a tempo Determinato) at University of Bari. In my research project I will investigate techniques for Semantic Holistic User Modeling.

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Last Update: September 1, 2014

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Last Update: March, 1 2017

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JANUARY 2016 - I'm Assistant Professor (Ricercatore a tempo Determinato) at University of Bari. In my research project I will investigate techniques for Semantic Holistic User Modeling.
JANUARY 2013 - I got a post-doc at University of Bari. My research was focused on techniques for semantic context-aware recommender systems based on distributional models.

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Research Assistant, Ph.D.

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

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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 proles. 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)

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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 proles. 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)

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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. Ex-

ploiting 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 proles. 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)

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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 proles. 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)

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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)

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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)

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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)

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encyclopedic knowledge for transparent and serendipitous user proles. 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)

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encyclopedic knowledge for transparent and serendipitous user proles. 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)

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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. Ex-

ploiting 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 proles. 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)

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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)

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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)

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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

to:

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)

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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.

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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)

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(download PDF)

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(download PDF)

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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.
P. Lops, M. de Gemmis, G. Semeraro, F. Narducci, and C. Musto. Leveraging the linkedin social network data for extracting content-based user profiles. 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)

to:

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 profiles. 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)

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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.
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.
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)

to:

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)

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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 Int�l Joint Conf. on Web Intelligence & Intelligent Agent Technology (WI-IAT 2009) LOS ALAMITOS, CA � USA: IEEE Computer Society Press. (download PDF)

to:

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 Int�l Joint Conf. on Web Intelligence & Intelligent Agent Technology (WI-IAT 2009) LOS ALAMITOS, CA � USA: IEEE Computer Society Press. (download PDF)

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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)

to:

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)

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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.

to:

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)

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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.

to:

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)

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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 Int�l Joint Conf. on Web Intelligence & Intelligent Agent Technology (WI-IAT 2009) LOS ALAMITOS, CA � USA: IEEE Computer Society Press.
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).

to:

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 Int�l Joint Conf. on Web Intelligence & Intelligent Agent Technology (WI-IAT 2009) LOS ALAMITOS, CA � 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)

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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.
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 classication. In IIR, pages 179-182. 2012.

to:

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 classication. In IIR, pages 179-182. 2012. (download PDF)

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My Curriculum Vitae Download (PDF)

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https://scontent-b.xx.fbcdn.net/hphotos-xfa1/v/t1.0-9/10599640_10204522471322183_8827979306029200008_n.jpg?oh=e87d9ebfb0068527d4da22e3155bb44a&oe=54649E5E

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Thesis: PDF

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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)

to:

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)

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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. (To appear)
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)

to:

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)

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My Curriculum Vitae Attach:musto-cv.pdf Δ

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My Curriculum Vitae (to be uploaded)

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My Curriculum Vitae Attach:musto-cv.pdf Δ

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Ph.D., Research Assistant

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Research Assistant, Ph.D.

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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. [[http://dl.acm.org/authorize?390064|(download PDF)]

to:

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)

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P. Lops, 'C. Musto', F. Narducci, M. de Gemmis, P. Basile, and G. Semeraro. Learning semantic content-based proles for cross-language personalization. In Proceedings of the Workshop on Personalized Multimedia Hypertext Retrieval (PMHR11). June 6 2011. [[http://dl.acm.org/authorize?6592317|(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. [[[[http://dl.acm.org/authorize?389116|(download PDF)]

to:

P. Lops, 'C. Musto', F. Narducci, M. de Gemmis, P. Basile, and G. Semeraro. Learning semantic content-based proles 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.

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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.

to:

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. [[http://dl.acm.org/authorize?390064|(download PDF)]

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P. Lops, 'C. Musto', F. Narducci, M. de Gemmis, P. Basile, and G. Semeraro. Learning semantic content-based proles for cross-language personalization. In Proceedings of the Workshop on Personalized Multimedia Hypertext Retrieval (PMHR11). June 6 2011.
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.

to:

P. Lops, 'C. Musto', F. Narducci, M. de Gemmis, P. Basile, and G. Semeraro. Learning semantic content-based proles for cross-language personalization. In Proceedings of the Workshop on Personalized Multimedia Hypertext Retrieval (PMHR11). June 6 2011. [[http://dl.acm.org/authorize?6592317|(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. [[[[http://dl.acm.org/authorize?389116|(download PDF)]

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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.

to:

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)

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P. Lops, M. de Gemmis, G. Semeraro, F. Narducci, and C. Musto. Leveraging the linkedin social network data for extracting content-based user profiles. In B. Mobasher, R. D. Burke, D. Jannach, and G. Adomavicius, editors, RecSys, pages 293-296. ACM, 2011. ISBN 978-1-4503-0683-6.

to:

P. Lops, M. de Gemmis, G. Semeraro, F. Narducci, and C. Musto. Leveraging the linkedin social network data for extracting content-based user profiles. 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)

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My Curriculum Vitae download PDF ?

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My Curriculum Vitae (to be uploaded)

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Thesis: download PDF ?

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Thesis: (to be uploaded)

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My Curriculum Vitae download PDF ?

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C. Musto, G. Semeraro, P. Lops, M. de Gemmis, and F. Narducci. Le-

veraging 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.

to:

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.

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C. Musto, F. Narducci, P. Lops, M. de Gemmis. Combining Collaborative and Content-based Techniques for Tag Recommendation. In E-Commerce and Web Technologies, 11th International Conference, EC-Web 2010, Bilbao, Spain, August 30 - September 3, 2010 - (to appear)

to:

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.

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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.
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 classication. In IIR, pages 179-182. 2012.
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.
P. Lops, 'C. Musto', F. Narducci, M. de Gemmis, P. Basile, and G. Semeraro. Learning semantic content-based proles for cross-language personalization. In Proceedings of the Workshop on Personalized Multimedia Hypertext Retrieval (PMHR11). June 6 2011.
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.

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C. Musto, F. Narducci, M. de Gemmis, P. Lops, G. Semeraro. A Tag Recommender System Exploiting User and Community Behavior. In Proceedings of the ACM RecSys 2009 Workshop on Recommender Systems & The Social Web. NEW YORK: Association for Computing Machinery, Inc. (ACM). To appear.

to:

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.

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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. To appear.

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Ph.D.

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Ph.D., Research Assistant

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Thesis: download PDF ?

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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.
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.

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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 The 14th International Conference on Artificial Intelligence: Methodology, Systems, Applications, AIMSA 2010, Varna, Bulgaria, September 8-10, 2010 - (to appear)

to:

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.
C. Musto, G. Semeraro, P. Lops, M. de Gemmis, and F. Narducci. Le-

veraging 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.

P. Lops, M. de Gemmis, G. Semeraro, F. Narducci, and C. Musto. Leveraging the linkedin social network data for extracting content-based user profiles. In B. Mobasher, R. D. Burke, D. Jannach, and G. Adomavicius, editors, RecSys, pages 293-296. ACM, 2011. ISBN 978-1-4503-0683-6.
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.
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.
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.
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.

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<div class="acmdlitem" id="item2362405"><img src="http://dl.acm.org/images/oa.gif25" height="25" border="0" alt="ACM DL Author-ize service" style="vertical-align:middle"/><a href="http://dl.acm.org/authorize?6858000" title="A folksonomy-based recommender system for personalized access to digital artworks">A folksonomy-based recommender system for personalized access to digital artworks</a><div style="margin-left:25px"><a href="http://dl.acm.org/author_page.cfm?id=81548022699" >Giovanni Semeraro</a>, <a href="http://dl.acm.org/author_page.cfm?id=81100585382" >Pasquale Lops</a>, <a href="http://dl.acm.org/author_page.cfm?id=81381593766" >Marco De Gemmis</a>, <a href="http://dl.acm.org/author_page.cfm?id=81442617077" >Cataldo Musto</a>, <a href="http://dl.acm.org/author_page.cfm?id=81442614611" >Fedelucio Narducci</a><br />Journal on Computing and Cultural Heritage (JOCCH), 2012</div></div>  <div class="acmdlstat" id ="stats2362405"><iframe src="http://dl.acm.org/authorizestats?6858000" width="100%" height="30" scrolling="no" frameborder="0">frames are not supported</iframe></div>

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Download PDF

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<div class="acmdlitem" id="item2362405"><img src="http://dl.acm.org/images/oa.gif25" height="25" border="0" alt="ACM DL Author-ize service" style="vertical-align:middle"/><a href="http://dl.acm.org/authorize?6858000" title="A folksonomy-based recommender system for personalized access to digital artworks">A folksonomy-based recommender system for personalized access to digital artworks</a><div style="margin-left:25px"><a href="http://dl.acm.org/author_page.cfm?id=81548022699" >Giovanni Semeraro</a>, <a href="http://dl.acm.org/author_page.cfm?id=81100585382" >Pasquale Lops</a>, <a href="http://dl.acm.org/author_page.cfm?id=81381593766" >Marco De Gemmis</a>, <a href="http://dl.acm.org/author_page.cfm?id=81442617077" >Cataldo Musto</a>, <a href="http://dl.acm.org/author_page.cfm?id=81442614611" >Fedelucio Narducci</a><br />Journal on Computing and Cultural Heritage (JOCCH), 2012</div></div>  <div class="acmdlstat" id ="stats2362405"><iframe src="http://dl.acm.org/authorizestats?6858000" width="100%" height="30" scrolling="no" frameborder="0">frames are not supported</iframe></div>

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Supervisor: prof. Giovanni Semeraro

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Supervisor: prof. Giovanni Semeraro

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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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2009/10 - Corso di Linguaggi di Programmazione + Lab. - CdL in Informatica - (Link) - (Join Facebook Group)

to:

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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My Curriculum Vitae (to be uploaded)

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Supervisor: prof. Giovanni Semeraro
Thesis: (to be uploaded)
Dissertation: YouTube (partial)
Presentation: Slideshare

to:

Supervisor: prof. Giovanni Semeraro
Thesis: (to be uploaded)
Dissertation: YouTube (partial)
Presentation: Slideshare

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Research Interests and Activities | Short Curriculum | Publications | Tools | Links

to:

Research Interests | Short Curriculum | Publications | Tools | Links

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Intelligent Information Access

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Hybrid Recommendation Strategies
Machine Learning Techniques for Recommender Systems

Personalization

User Modeling and Profiling
Semantic Web Personalization

Web 2.0

Recommender Systems for Web 2.0
Recommender Systems in the Big Data era

to:

Distributional Semantics
Social Media and Linked Data for User Modeling
Recommender Systems and Big Data

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Title: Enhanced Vector Space Models for Content-based Recommender Systems

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Title: Enhanced Vector Space Models for Content-based Recommender Systems

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Dissertation: YouTube link (partial)
Presentation: Slideshare link

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Dissertation: YouTube (partial)
Presentation: Slideshare

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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″.

(A part of my Ph.D. defense)

to:

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″

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Ph.D.

Title: Enhanced Vector Space Models for Content-based Recommender Systems
Supervisor: prof. Giovanni Semeraro
Thesis: (to be uploaded)
Dissertation: YouTube link (partial)
Presentation: Slideshare link

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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″.(A part of my Ph.D. defense)

to:

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″.

(A part of my Ph.D. defense)

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A part of my (Ph.D. defense) on YouTube

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A part of my Ph.D. defense on YouTube
Twitter account

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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″.

to:

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″.(A part of my Ph.D. defense)

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My presentations on Slideshare

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My presentations on Slideshare
A part of my (Ph.D. defense) on YouTube

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My publications on DBLP

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My Google Scholar profile

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My publications on DBLP

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My presentations on Slideshare \\\

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My Google Scholar profile

* My presentations on Slideshare

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My publications on DBLP

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My presentations on Slideshare

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Links My publications on DBLP

My Google Scholar profile

My presentations on Slideshare \\\

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My Google Scholar profile

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My http://www.slideshare.net/cataldo presentations on Slideshare

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My presentations on Slideshare

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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.

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UMAP 2012 I received a $1000 student grant to attend the conference and present a paper at the Industrial track.

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My http://scholar.google.com/citations?user=pauGgdYAAAAJ profile

My http://www.slideshare.net/cataldo presentations on Slideshare

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Ph.D. Student

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Ph.D.

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e-mail: cataldomusto___AT___di.uniba.it

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e-mail: cataldo.musto___AT___uniba.it

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Recommender Systems in the Big Data era

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Last Update: September 3, 2010

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Last Update: September 19, 2012

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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″.

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FIRSt. Folksonomy-based ITem Recommender is a content-based item recommending on the basis of ratings given by users. It use a Na�ve 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 - TRY IT!

to:

FIRSt. Folksonomy-based ITem Recommender is a content-based item recommending on the basis of ratings given by users. It use a Na�ve 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

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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 The 14th International Conference on Artificial Intelligence: Methodology, Systems, Applications, AIMSA 2010, Varna, Bulgaria, September 8-10, 2010 - (to appear)

September 03, 2010, at 05:59 AM EST by 130.206.138.231 -

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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

to:

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

September 03, 2010, at 05:59 AM EST by 130.206.138.231 -

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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.

to:

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.

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heritage personalization In: Proceedings of the 6th Italian Research Con- ference on Digital Libraries - IRCDL 2010, Padua, Italy, January 28-29, 2010.

to:

heritage personalization In: Proceedings of the 6th Italian Research Conference on Digital Libraries - IRCDL 2010, Padua, Italy, January 28-29, 2010.

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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)

to:

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)

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C.Musto, F. Narducci, P. Lops, M. de Gemmis, G. Semeraro. Exploit-

ing content-based recommender systems and digital libraries for cultural

to:

C.Musto, F. Narducci, P. Lops, M. de Gemmis, G. Semeraro. Exploiting content-based recommender systems and digital libraries for cultural

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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. (To appear)

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.

to:

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. (To appear)
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.

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Last Update: September 3, 2010

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Last Update: September 3, 2010

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M. de Gemmis, L. Iaquinta, P. Lops, C. Musto, F. Narducci, G. Semeraro. Learning Preference Models in Recommender Systems. In Preference Learning. Springer, 2009. To appear.
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 Web Personalization in Intelligent Environment. Springer, 2009. To appear.

to:

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. (To appear)

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)

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C. Musto, F. Narducci, P. Lops, M. de Gemmis. Combining Collaborative and Content-based Techniques for Tag Recommendation. In E-Commerce and Web Technologies, 11th International Conference, EC-Web 2010, Bilbao, Spain, August 30 - September 3, 2010 - (to appear)
C.Musto, F. Narducci, P. Lops, M. de Gemmis, G. Semeraro. Exploit-

ing content-based recommender systems and digital libraries for cultural heritage personalization In: Proceedings of the 6th Italian Research Con- ference on Digital Libraries - IRCDL 2010, Padua, Italy, January 28-29, 2010.

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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 Int�l Joint Conf. on Web Intelligence & Intelligent Agent Technology (WI-IAT 2009) LOS ALAMITOS, CA � USA: IEEE Computer Society Press. To appear.
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). To appear.
C. Musto, F. Narducci, M. de Gemmis, P. Lops, G. Semeraro. A Tag Recommender System Exploiting User and Community Behavior. In Proceedings of the ACM RecSys 2009 Workshop on Recommender Systems & The Social Web. NEW YORK: Association for Computing Machinery, Inc. (ACM). To appear.

to:

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 Int�l Joint Conf. on Web Intelligence & Intelligent Agent Technology (WI-IAT 2009) LOS ALAMITOS, CA � USA: IEEE Computer Society Press.
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).

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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

C. Musto, F. Narducci, M. de Gemmis, P. Lops, G. Semeraro. A Tag Recommender System Exploiting User and Community Behavior. In Proceedings of the ACM RecSys 2009 Workshop on Recommender Systems & The Social Web. NEW YORK: Association for Computing Machinery, Inc. (ACM). To appear.

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SSSC 2010 - IEEE 2010 Summer School on Semantic Computing - Berkeley (CA, United States), July 25-31, 2010 - 1st prize award (link) for the contribution within the Student Project work 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.

to:

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.

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2009/10 - Basi di Dati - (Link)
2009/10 - Linguaggi di Programmazione + Lab. - (Link) , (Join Facebook Group)

to:

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) - (Join Facebook Group)

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Summer Schools

to:

Summer Schools

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Awards

SSSC 2010 - IEEE 2010 Summer School on Semantic Computing - Berkeley (CA, United States), July 25-31, 2010 - 1st prize award link for the contribution within the Student Project work 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

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

to:

Awards

SSSC 2010 - IEEE 2010 Summer School on Semantic Computing - Berkeley (CA, United States), July 25-31, 2010 - 1st prize award (link) for the contribution within the Student Project work 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 - Basi di Dati - (Link)
2009/10 - Linguaggi di Programmazione + Lab. - (Link) , (Join Facebook Group)

September 03, 2010, at 05:30 AM EST by 130.206.138.231 -

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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

SSSC 2010 - IEEE 2010 Summer School on Semantic Computing - Berkeley (CA, United States), July 25-31, 2010 - 1st prize award link for the contribution within the Student Project work 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

September 03, 2010, at 05:23 AM EST by 130.206.138.231 -

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Last Update: September 3, 2010

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September 03, 2010, at 05:22 AM EST by 130.206.138.231 -

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My publications on DBLP

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ACAI 2009 - Advanced Course in Artificial Intelligence '09 Intelligent Decision Support Systems (theory, algorithms, and applications) - Belfast, August 23-29, 2009

to:

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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Thanks to Marica for the photo :-)

February 25, 2010, at 10:49 AM EST by 193.204.187.151 -

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FIRST. Folksonomy-based ITem Recommender is a content-based item recommending on the basis of ratings given by users. It use a Na�ve 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 - TRY IT!

to:

FIRSt. Folksonomy-based ITem Recommender is a content-based item recommending on the basis of ratings given by users. It use a Na�ve 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 - TRY IT!

February 25, 2010, at 10:48 AM EST by 193.204.187.151 -

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ITR. ITem Recommender is a content-based item recommending on the basis of ratings given by users. It use a Na�ve 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.

to:

FIRST. Folksonomy-based ITem Recommender is a content-based item recommending on the basis of ratings given by users. It use a Na�ve 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 - TRY IT!

Membri.CataldoMusto History