Abstract
Recommender Systems try to assist users to access complex information spaces regarding their long term needs and preferences. Various recommendation techniques have been investigated and each one has its own strengths and weaknesses. Especially, content-based techniques suffer of overspecialization problem. We propose to inject diversity in the recommendation task by exploiting the content-based user profile to spot potential surprising suggestions. In addition, the actual selection of serendipitous items is motivated by an applicative scenario. Thus, the reference scenario concerns personalized tours in a museum and serendipitous items are introduced by slight diversions on the context-aware tours.
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References
André, P., Schraefel, m.c., Teevan, J., Dumais, S.T.: Discovery is never by chance: designing for (un)serendipity. In: Proceeding of the 7th ACM Conference on Creativity and Cognition (C&C 2009), pp. 305–314. ACM, New York (2009), doi:10.1145/1640233.1640279
Campos, J., de Figueiredo, A.: Searching the unsearchable: Inducing serendipitous insights. In: Weber, R., Gresse, C. (eds.) Proceedings of the Workshop Program at the 4th International Conference on Case-Based Reasoning (ICCBR 2001), pp. 159–164 (2001)
Cosley, D., Lawrence, S., Pennock, D.M.: REFEREE: An open framework for practical testing of recommender systems using researchindex. In: Proceedings of 28th International Conference on Very Large Data Bases (VLDB 2002), pp. 35–46. Morgan Kaufmann, San Francisco (2002)
De Bono, E.: Lateral Thinking: A Textbook of Creativity. Penguin Books, London (1990)
Foster, A., Ford, N.: Serendipity and information seeking: an empirical study. Journal of Documentation 59(3), 321–340 (2003)
Ge, M., Delgado-Battenfeld, C., Jannach, D.: Beyond accuracy: evaluating recommender systems by coverage and serendipity. In: Proceedings of the 4th ACM Conference on Recommender Systems (RecSys 2010), pp. 257–260. ACM, New York (2010), doi:10.1145/1864708.1864761
Herlocker, J.L., Konstan, J.A., Terveen, L.G., Riedl, J.T.: Evaluating collaborative filtering recommender systems. ACM Transactions on Information Systems 22(1), 5–53 (2004), doi:10.1145/963770.963772
Iaquinta, L., de Gemmis, M., Lops, P., Semeraro, G., Molino, P.: Can a recommender system induce serendipitous encounters? In: Kang, K. (ed.) E-Commerce, pp. 227–243. In-Teh (2010)
Marchionini, G., Shneiderman, B.: Finding facts vs. browsing knowledge in hypertext systems. Computer 21(1), 70–80 (1988), doi:10.1109/2.222119
Mehta, B., Niederée, C., Stewart, A., Degemmis, M., Lops, P., Semeraro, G.: Ontologically-enriched unified user modeling for cross-system personalization. In: Ardissono, L., Brna, P., Mitrović, A. (eds.) UM 2005. LNCS (LNAI), vol. 3538, pp. 119–123. Springer, Heidelberg (2005), doi:10.1007/11527886_16
Roberts, R.M.: Serendipity: Accidental Discoveries in Science. John Wiley & Sons, Chichester (1989)
Shani, G., Gunawardana, A.: Evaluating recommendation systems. In: Ricci, P.B.F., Rokach, L., Shapira, B., Kantor (eds.) Recommender Systems Handbook, pp. 257–297. Springer, Heidelberg (2011), doi:10.1007/978-0-387-85820-3_8
Toms, E.G.: Serendipitous information retrieval. In: DELOS Workshop: Information Seeking, Searching and Querying in Digital Libraries (2000)
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Iaquinta, L., de Gemmis, M., Lops, P., Semeraro, G., Molino, P. (2011). Motivating Serendipitous Encounters in Museum Recommendations. In: Pallotta, V., Soro, A., Vargiu, E. (eds) Advances in Distributed Agent-Based Retrieval Tools. Studies in Computational Intelligence, vol 361. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21384-7_11
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DOI: https://doi.org/10.1007/978-3-642-21384-7_11
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