Abstract
This paper describes a multiagent recommender system where agents maintain local knowledge bases and, when requested to support a travel planning task, they collaborate exchanging information stored in their local bases. A request for a travel recommendation is decomposed by the system into sub tasks, corresponding to travel services. Agents select tasks autonomously, and accomplish them with the help of the knowledge derived from previous solutions. In the proposed architecture, agents become experts in some task types, and this makes the recommendation generation more efficient. In this paper, we validate the model via simulations where agents collaborate to recommend a travel package to the user. The experiments show that specialization is useful hence providing a validation of the proposed model.
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References
Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering 17(6), 734–749 (2005)
Balabanovic, M., Shoham, Y.: Fab: Content-based, collaborative recommendation. Communications of the Association for Computing Machinery 40(3), 66–72 (1997)
Bellifemine, F., Caire, G., Greenwood, D.: Developing Multi-Agent Systems with JADE. Wiley, Chichester (2007)
Billsus, D., Pazzani, M.: A hybrid user model for news story classification. In: Proceedings of the Seventh International Conference on User Modeling, UM 1999, Banff, Canada (1999)
Goy, A., Ardissono, L., Petrone, G.: Personalization in e-commerce applications. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) Adaptive Web 2007. LNCS, vol. 4321, pp. 485–520. Springer, Heidelberg (2007)
Lorenzi, F., Ricci, F.: Case-based recommender systems: a unifying view. In: Mobasher, B., Anand, S. (eds.) Intelligent Techniques for Web Personalization, pp. 89–113. Springer, Heidelberg (2005)
Lorenzi, F., Santos, D.S., de Oliveira, D., Bazzan, A.L.C.: Task allocation in case-based recommender systems: a swarm intelligence approach. In: Lin, H. (ed.) Architectural Design of Multi-Agent Systems. Information Science Reference, pp. 268–279 (2007)
Macho, S., Torrens, M., Faltings, B.: A multi-agent recommender system for planning meetings. In: Workshop on Agent-based recommender systems (2000)
Maes, P.: Agents that reduce work and information overload. Commun. ACM 37(7), 30–40 (1994)
Montaner, M., López, B., de la Rosa, J.L.: A taxonomy of recommender agents on the internet. Artificial Intelligence Review 19(4), 285–330 (2003)
Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., Riedl, J.: Grouplens: An open architecture for collaborative filtering of netnews. In: Proceedings ACM Conference on Computer-Supported Cooperative Work, pp. 175–186 (1994)
Ricci, F.: Travel recommender systems. IEEE Intelligent Systems 17(6), 55–57 (2002)
Schafer, J., Konstan, J., Riedl, J.: E-commerce recommendation applications. Data Mining and Knowledge Discovery 5(1/2), 115–153 (2001)
Smyth, B.: Case-based recommendation. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) Adaptive Web 2007. LNCS, vol. 4321, pp. 342–376. Springer, Heidelberg (2007)
Sycara, K.: Multiagents systems. AI Magazine 19(2), 79–82 (1998)
Wei, Y., Moreau, L., Jennings, N.: Recommender systems: A market-based design. In: Proceedings Second International Joint Conference on Autonomous Agents and Multi Agent Systems (AAMAS 2003), Melbourne, Australia, July 2003, pp. 600–607 (2003)
Werthner, H., Ricci, F.: E-commerce and tourism. Commun. ACM 47(12), 101–105 (2004)
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Lorenzi, F., Correa, F.A.C., Bazzan, A.L.C., Abel, M., Ricci, F. (2010). A Multiagent Recommender System with Task-Based Agent Specialization. In: Ketter, W., La Poutré, H., Sadeh, N., Shehory, O., Walsh, W. (eds) Agent-Mediated Electronic Commerce and Trading Agent Design and Analysis. AMEC TADA 2008 2008. Lecture Notes in Business Information Processing, vol 44. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15237-5_8
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DOI: https://doi.org/10.1007/978-3-642-15237-5_8
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