International Journal of Information Science

International Journal of Information Science is a peer-reviewed journal that publishes original papers of high scientific value in all areas of information science. The journal publishes high-quality, refereed articles. It emphasizes a balanced coverage of both theory and practice. It fully acknowledges and vividly promotes a breadth of the discipline of information sciences.

Umberto Panniello

Editorial Board Member of International Journal of Information Science

Post-doctoral Fellow, Polytechnic of Bari, Italy

Research Areas

Customer Relationship Management, Data Mining models for E-commerce

Education

2008-2010PhDPhD in Business and Management Engineering, Polytechnic of Bari
2004-2007Master Degree Master Degree in Business Engineering, Polytechnic of Bari, Italy
2001-2004Bachelor DegreeBachelor Degree in Business Engineering, Polytechnic of Bari, Italy

Experience

2010Personalized marketing actions for users with high churn probability in a bank, Banca Popolare di Bari (Bank of Bari)
2009Predictive models for the prevention of the customer churn in a bank, Banca Popolare di Bari (Bank of Bari)
2008-2010Panini S.p.A., Modena
2008Study of the formative gap in the sectors: TAC, food and tourism, Polytechnic of Bari
2007Business plan for the realization of a garbage disposal plant, Polytechnic of Bari

Publications: Conferences/Workshops/Symposiums/Journals/Books

[1]  Panniello, U., Gorgoglione, M., Beyond customer churn: generating personalized actions to retain customers in a retail bank by a recommender system approach, Journal of Intelligent Systems and Application, vol. 3, n. 2, pp. 90-102, 2011.
[2]  Panniello, U., Gorgoglione, M., Incorporating Context Into Recommender Systems: An Empirical Comparison Of Context-Based Approaches. Accepted for publication Electronic Commerce Research, 2011.
[3]  Gorgoglione, M., Panniello, U., Tuzhilin, A., The Effect of Context-Aware Recommendations on Customer Purchasing Behavior and Trust, 5th ACM conference on Recommender Systems, Chicago, USA, October 23-27, 2011.
[4]  Panniello, U., Gorgoglione, M., A Contextual Modeling Approach to Context-Aware Recommender Systems, CARS 2011, Chicago, USA, October 23-27, 2011.
[5]  Panniello, U., Gorgoglione, M., Does the recommendation task affect a CARS performance?, 4th ACM conference on Recommender Systems, Barcellona, Spain, September 2010.
[6]  Gorgoglione, M., Panniello, U., Experimental Comparison of Three Approaches to Context-Aware Recommender Systems, XXI AiIG Annual Conference, L'Aquila, Italy, October 14-15, 2010.
[7]  Panniello, U., Tuzhilin, A., Gorgoglione, M., Palmisano, C., Pedone, A., Experimental Comparison of Pre-vs. Post-Filtering Approaches in Context-Aware Recommender Systems, 3rd ACM Conference on Recommender Systems, New York, USA, October 2009.
[8]  Panniello, U., Gorgoglione, M., Palmisano, C., Comparing Pre-Filtering and Post-Filtering Approach in a Collaborative Contextual Recommender System: an Application to E-Commerce, 10th International Conference on Electronic Commerce and Web, Linz, Austria, September 2009.
[9]  Gorgoglione, M., Panniello, U., Including Context in a Transactional Recommender System Using a Pre-Filtering Approach: Two Real E-Commerce Applications, The 2009 IEEE International Symposium on Mining and Web, Bradford, UK, May 2009.
[10]  Gorgoglione, M., Faraone, M.F., Lombardi, S., Panniello, U., Tuzhilin, A., Palmisano, C., The effect of context on the predictive performance of segmentation, WIIAT WPRRS Workshop, Sydney, Australia, December 2008.