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A Fuzzy Trust Model for Argumentation-Based Recommender Systems

Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 130)

Abstract

With the enormous growth of the Internet and Agent-based E-commerce, online trust has become an increasingly important issue. The fact that multi-agent systems are vulnerable with respect to malicious agents poses a great challenge: the detection and the prevention of undesirable behaviors. That is the reason why techniques such as trust and reputation mechanisms have been used in literature. In this paper, we propose a fuzzy trust model for argumentation-based open multi-agent recommender systems. In an open Agent-based Recommender System, the goals of agents acting on behalf of their owners often conflict with each other. Therefore, a personal agent protecting the interest of a single user cannot always rely on them. Consequently, such a personal agent needs to determine whether to trust (information or services provided by) other agents or not. Lack of a trust computation mechanism may hinder the acceptance of agent-based technologies in sensitive applications where users need to rely on their personal agents. Against this background, we propose an extension of the basic argumentation framework in Agent-Based Recommender Systems to use the fuzzy trust within these models for trustworthy recommendations.

Keywords

Intelligent Agents Recommendation Agents Trust Argumentation Framework Fuzzy logic 

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References

  1. 1.
    Andersen, R., Borgs, C., Chayes, J., Feige, U., Flaxman, A., Kalai, A., Mirrokni, V., Tennenholtz, M.: Trust-Based Recommendation Systems: an Axiomatic Approach, WWW 2008, Refereed Track: Internet Monetization - Recommendation & Security (April 21-25, 2008)Google Scholar
  2. 2.
    Bedi, P., Vashisth, P.: Interest Based Recommendations with Argumentation. Journal of Artificial Intelligence, ANSI, 119–142 (2011)Google Scholar
  3. 3.
    Bedi, P., Vashisth, P.: Social-cognitive trust integrated in agents for E-commerce. In: Proceedings of the 2nd IC4E, Mumbai, India, January 7-9, pp. 1–11 (2011)Google Scholar
  4. 4.
    Bentahar, J., Meyer, J.J.C.: A New Quantitative Trust Model for Negotiating Agents using Argumentation. International Journal of Computer Science & Applications IV(II), 1–21 (2006)Google Scholar
  5. 5.
    Bharadwaj, K.K., Al-Shamri, M.Y.H.: Fuzzy computational models for trust and reputation systems. Electron. Comm. Res. Appl. (2008), doi:10.1016/j.elerap.2008.08.001Google Scholar
  6. 6.
    Chesnevar, C., Maguitman, A.G., Gonzalez, M.P.: Empowering Recommendation Technologies Through Argumentation. In: Argumentation in Artificial Intelligence, p. 504. Springer, Heidelberg (2009) ISBN-13: 978-0387981963Google Scholar
  7. 7.
    Parsons, S., Tang, Y., Sklar, E., McBurney, P., Cai, K.: Argumentation-based reasoning in agents with varying degrees of trust. In: Proc. of 10th Int. Conf. on Autonomous Agents and Multiagent Systems, AAMAS, pp. 879–886 (2011)Google Scholar
  8. 8.
    Stranders, R., de Weerdt, M., Witteveen, C.: Fuzzy Argumentation for Trust. In: Sadri, F., Satoh, K. (eds.) CLIMA VIII 2007. LNCS (LNAI), vol. 5056, pp. 214–230. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  9. 9.
    Tang, Y., Cai, K., Sklar, E., McBurney, P., Parsons, S.: A system of argumentation for reasoning about trust. In: Proceedings of the 8th European Workshop on Multi-Agent Systems, Paris, France (2010)Google Scholar
  10. 10.
    Wei, Z.: A Novel Trust Model Based on Recommendation for E-commerce. IEEE (2007) 1-4244-0885-7Google Scholar
  11. 11.
    Zadeh, L.A.: A computational approach to fuzzy quantifiers in natural languages. Computer and Mathematics with Applications 9(1), 149–184 (1983)MathSciNetMATHCrossRefGoogle Scholar

Copyright information

© Springer India Pvt. Ltd. 2012

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of DelhiDelhiIndia

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