Abstract
In the last years, Business-to-Consumer (B2C) E-Commerce is playing a key role in the Web. In this scenario, recommender systems appear as a promising solution for both merchants and customers. However, in this context, the low scalability of the performances and the dependence on a centralized platform are two key problems to face. In this paper, we present a novel recommender system based on a multi-agent architecture, called Trader REcommender Systems (TRES). In TRES, the agents exploit their user’s profiles in their interaction, to make the merchants capable to generate effective and efficient recommendations. The architecture we have adopted is fully decentralized, giving to each merchant the capability to generate recommendations without requiring the help of any centralized computational unit. This characteristic, on the one hand, makes the system scalable with respect to the size of the users’ community. On the other hand, the privacy of each customer is preserved, since the merchant retrieves information about each customer simply monitoring the customer behaviour in visiting his site.To show the advantages introduced by the proposed approach some experimental results carried out by exploiting a prototype implemented in the JADE framework are presented.
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References
Kauffman, R.J., Walden, E.A.: Economics and Electronic Commerce: Survey and Directions for Research. International Journal of Electronic Commerce 5(4), 5–116 (2001)
Zwass, V.: Electronic Commerce and Organizational Innovation: Aspects and Opportunities. International Journal of Electronic Commerce 7(3), 7–37 (2003)
Sarwar, B., Karypis, G., Konstan, J., Riedl, J.: Analysis of Recommendation Algorithms for E-Commerce. In: Proceedings of the 2nd ACM Conference on Electronic Commerce (EC 2000), pp. 158–167. ACM, New York (2000)
Schafer, J.B., Konstan, J.A., Riedl, J.: E-Commerce Recommendation Applications. Data Mining Knowledge Discovery 5(1-2), 115–153 (2001)
Burke, R.D.: Hybrid Recommender Systems: Survey and Experiments. User Modeling and User-Adapted Interaction 12(4), 331–370 (2002)
Montaner, M., Lopez, B., de la Rosa, J.L.: A Taxonomy of Recommender Agents on the Internet. Journal of Web Semantics (JWS) 19(4), 285–330 (2004)
Wei, K., Huang, J., Fu, S.: A Survey of E-Commerce Recommender Systems. In: Proceedings of the 13th International Conference on Service Systems and Service Management, pp. 1–5. IEEE Computer Society, Washington, DC (2007)
Nicosia, F.: Consumer Decision Processes: Marketing and Advertising Implications. Prentice Hall, New York (1966)
Engel, J.F., Blackwell, R.D., Miniard, P.W.: Consumer Behaviour. International ed. The Dryden Press, London, UK (1995)
Nissen, M.E.: The Commerce Model for Electronic Redesign. J. of Internet Purchasing 1(2) (1997), http://www.arraydev.com/commerce/JIP/9702--01.htm
Feldman, S.: The Objects of the E-Commerce, Keynote speech at ACM 1999 Conference on OOPLSA, Denver (1999), http://www.ibm.com/iac/oopsla99-sifkeynote.pdf
Guttman, R.H., Moukas, A., Maes, P.: Agents as Mediators in Electronic Commerce. Electronic Markets 8(1) (1998)
He, M., Jennings, N.R., Leung, H.: On Agent-Mediated Electronic Commerce. IEEE Transaction Knowledge Data Engineering 15(4), 985–1003 (2003)
Palopoli, L., Rosaci, D., Ursino, D.: Agents’ Roles in B2C e-Commerce. AI Communication 19(2), 95–126 (2006)
Maes, P.: Agents that Reduce Work and Information Overload. Communication of ACM 37(7), 30–40 (1994)
Hayes-Roth, B.: An Architecture for Adaptive Intelligent Systems. Artificial Intelligence 72(1-2), 329–365 (1995)
Wooldridge, M., Jennings, N.R.: Agent Theories, Architectures, and Languages: A Survey. In: Wooldridge, M.J., Jennings, N.R. (eds.) ECAI 1994 and ATAL 1994. LNCS, vol. 890, pp. 1–39. Springer, Heidelberg (1995)
Franklin, S., Graesser, A.C.: Is it an Agent, or Just a Program?: A Taxonomy for Autonomous Agents. In: Jennings, N.R., Wooldridge, M.J., Müller, J.P. (eds.) ECAI-WS 1996 and ATAL 1996. LNCS, vol. 1193, pp. 21–35. Springer, Heidelberg (1997)
Gilbert, D., Aparicio, M., Atkinson, B., Brady, S., Ciocarino, J., Grosof, B., O’Connor, P., Osisek, D., Pritko, S., Spagna, R., Wilson, L.: White Paper on Intelligent Agents. IBM Report, Zurich, Switzerland (1996)
Nwana, H.S.: Software Agents: An Overview. Knowoledge Engineering Review 11(3), 11–40 (1996)
Russell, S.J.: Rationality and Intelligence. Artificial Intelligence 94(1-2), 57–77 (1997)
Iglesias, C.A., Garijo, M., González, J.C.: A Survey of Agent-Oriented Methodologies. In: Papadimitriou, C., Singh, M.P., Müller, J.P. (eds.) ATAL 1998. LNCS (LNAI), vol. 1555, pp. 317–330. Springer, Heidelberg (1999)
Extensible Markup Language (XML) v.e. 1.1 (2010), http://www.w3.org/TR/2004/REC-xml11-20040204
Grosof, B.N., Labrou, Y.: An Approach to Using XML and a Rule-Based Content Language with an Agent Communication Language. In: Dignum, F., Greaves, M. (eds.) Agent Communication. LNCS (LNAI), vol. 1916, pp. 96–117. Springer, Heidelberg (2000)
O’Brien, P.D., Nicol, R.C.: FIPA Towards a Standard for Software Agents. BT Technology Journal 16(3), 51–59 (1998)
Foundation for Intelligent Physical Agents (FIPA) - ACL URL. FIPA ACL Message Structure Specif. (2010), http://www.fipa.org/specs/fipa00061/
Melville, P., Mooney, R.J., Nagarajan, R.: Content-boosted Collaborative Filtering for Improved Recommendations. In: Proceedings of the 18th National Conference on Artificial Intelligence, Edmonton, Canada, pp. 187–192. AAAI/IAAI (2002)
Garruzzo, S., Modafferi, S., Rosaci, D., Ursino, D.: X-Compass: An XML Agent for Supporting User Navigation on the Web. In: Andreasen, T., Motro, A., Christiansen, H., Larsen, H.L. (eds.) FQAS 2002. LNCS (LNAI), vol. 2522, pp. 197–211. Springer, Heidelberg (2002)
North America Industry Classifications (NAICS) (2010), http://www.census.gov/naics/2007/index.html
Extensible Markup Language (XML) Schema (2010), http://www.w3.org/XML/Schema
Asokan, N., Janson, P.A., Steiner, M., Waidner, M.: The State of the Art in Electronic Payment Systems. IEEE Computer 30(9), 28–35 (1997)
O’Mahony, D., Pierce, M., Tewari, H.: Electronic Payment Systems for E-Commerce, 2nd edn. Artech House, Norwood (2001)
Balabanovic, M., Shoham, Y.: Content-Based, Collaborative Recommendation. Communication of ACM 40(3), 66–72 (1997)
Aggarwal, C.C., Yu, P.S.: Data Mining Techniques for Personalization. IEEE Data Engineering Bulletin 23(1), 4–9 (2000)
Lawrence, R.D., Almasi, G.S., Kotlyar, V., Viveros, M.S., Duri, S.: Personalization of Supermarket Product Recommendations. Data Mining Knowledge Discovery 5(1/2), 11–32 (2001)
Tso, K.H.L., Schmidt-Thieme, L.: Evaluation of Attribute-Aware Recommender System Algorithms on Data with Varying Characteristics. In: Ng, W.-K., Kitsuregawa, M., Li, J., Chang, K. (eds.) PAKDD 2006. LNCS (LNAI), vol. 3918, pp. 831–840. Springer, Heidelberg (2006)
Wei, C.P., Shaw, M.J., Easley, R.F.: A Survey of Recommendation Systems in Electonic Commerce. In: E-Service: New directions in Theory and Practice. ME Sharpe, Armonk (2002)
Manouselis, N., Costopoulou, C.: Analysis and Classification of Multi-Criteria Recommender Systems. World Wide Web 10(4), 415–441 (2007)
Birukov, A., Blanzieri, E., Giorgini, P.: Implicit: A Recommender System that Uses Implicit Knowledge to Produce Suggestions. In: Workshop on Multi-Agent Information Retrieval and Recommender Systems at the 19th International Joint Conference on Artificial Intelligence (IJCAI 2005), Edinburgh, Scotland (2005)
Rosaci, D., Sarnè, G.M.L.: MASHA: A Multi-Agent System Handling User and Device Adaptivity of Web Sites. User Modelling User-Adaptive Interaction 16(5), 435–462 (2006)
Guan, S., Ngoo, C.S., Zhu, F.: Handy broker: an Intelligent Product-Brokering Agent for m-Commerce Applications with User Preference Tracking. Electronic Commerce Research and Application 1(3-4), 314–330 (2002)
Lee, W.P.: Towards Agent-based Decision Making in the Electronic Marketplace: Interactive Recommendation and Automated Negotiation. Expert Systems with Applications 27(4), 665–679 (2004)
Silvestri, F., Baraglia, R., Palmerini, P., Serranó, M.: On-line Generation of Suggestions for Web Users. In: ITCC (1), pp. 392–397. IEEE Computer Society, Washington, DC (2004)
Huang, Z., Chung, W., Chen, H.: A graph model for e-commerce recommender systems. Journal of American Society Information Science Technology 55(3), 259–274 (2004)
Bellifemine, F., Poggi, A., Rimassa, G.: Developing Multi-Agent Systems with a FIPA-compliant Agent Framework. User Modelling User-Adaptive Interaction 12(4), 331–370 (2002)
Java Agent DEvelop. framew. (JADE) (2010), http://jade.tilab.com/
van Rijsbergen, C.J.: Information Retrieval. Butterworth (1979)
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Rosaci, D., Sarné, G.M.L. (2013). Generating B2C Recommendations Using a Fully Decentralized Architecture. In: Hakansson, A., Hartung, R. (eds) Agent and Multi-Agent Systems in Distributed Systems - Digital Economy and E-Commerce. Studies in Computational Intelligence, vol 462. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35208-9_9
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DOI: https://doi.org/10.1007/978-3-642-35208-9_9
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