ELM Predicting Trust from Reputation in a Social Network of Reviewers

Chapter
Part of the Adaptation, Learning, and Optimization book series (ALO, volume 16)

Abstract

Trust is a central concept in distributed systems, such as Ad Hoc Networks, Social Networks and Recommender Systems. Trust has a predictive component, it is a measure of the certainty that an agent has on the output from other agent. Hence, Trust is a key component of distributed decision making processes. It can be built from reputation, meaning the observation of the Trust values from other agents (the trusters) on the target agent (the trustee). In this chapter we take the point of view of predicting the Trust value on the basis of the reputation information that the agent may collect. When Trust values are categorical, or binary, the problem becomes a classification problem that can be tackled by Extreme Learning Machines (ELM). We perform experimental assessment of the value of ELM for this task on a benchmark database obtained from a real life recommender system.

Keywords

ELM Trust computation Recommender systems 

Notes

Acknowledgments

This research has been partially funded by EU through SandS project, grant agreement No. 317947.

References

  1. 1.
    B. Bhargava, L. Lilien, A. Rosenthal, M. Winslett, M. Sloman, T.S. Dillon, E. Chang, F.K. Hussain, W. Nejdl, D. Olmedilla, V. Kashyap, The pudding of trust. IEEE Intell. Syst. 19(5), 74–88 (2004)Google Scholar
  2. 2.
    N. Shadbolt, A matter of trust. IEEE Intell. Syst. 17(1), 2–3 (2002)Google Scholar
  3. 3.
    R.R. Hoffman, M. Johnson, J.M. Bradshaw, A. Underbrink, Trust in automation. IEEE Intell. Syst. 28(1), 84–88 (2013)Google Scholar
  4. 4.
    M.S. Lund, B. Solhaug, K. Stlen, Evolution in relation to risk and trust management. Computer 43(5), 49–55 (2010)Google Scholar
  5. 5.
    J. Ma, M.A. Orgun, Trust management and trust theory revision. IEEE Trans. Syst. Man Cybern. Part A Syst. Hum. 36(3), 451–460 (2006)Google Scholar
  6. 6.
    P. Massa, P. Avesani, Trust metrics in recommender systems, in Computing with Social Trust, ed. by J. Golbeck (Springer, Berlin, 2009), pp. 259–285Google Scholar
  7. 7.
    P. Victor, C. Cornelis, M.D. Cock, A.M. Teredesai, Trust- and distrust-based recommendations for controversial reviews. IEEE Intell. Syst. 26(1), 48–55 (2011)Google Scholar
  8. 8.
    K.S. Cook (ed.), Trust in Society. Russell Sage Foundation Series on Trust, vol. 2. (Russell Sage Foundation, New York, 2003)Google Scholar
  9. 9.
    S.I. Ahamed, M.M. Haque, Md.E. Hoque, F. Rahman, N. Talukder, Design, analysis, and deployment of omnipresent formal trust model (FTM) with trust bootstrapping for pervasive environments. J. Syst. Softw. 83(2), 253–270 (2010) (Comput. Softw. Appl.)Google Scholar
  10. 10.
    J. Golbeck, Computing with trust: definition, properties, and algorithms, in Securecomm and Workshops, 2006, pp. 1–7, 28 Aug 2006–1 Sept 2006Google Scholar
  11. 11.
    J.-H. Cho, A. Swami, I.-R. Chen, A survey on trust management for mobile ad hoc networks. IEEE Commun. Surv. Tutorials 13(4), 562–583 (2011)Google Scholar
  12. 12.
    X. Gai, Y. Li, Y. Chen, C. Shen, Formal definitions for trust in trusted computing, in 2010 7th International Conference on Ubiquitous Intelligence Computing and 7th International Conference on Autonomic Trusted Computing (UIC/ATC), pp. 305–310 (2010)Google Scholar
  13. 13.
    R.R. Hoffman, J.D. Lee, D.D. Woods, N. Shadbolt, J. Miller, J.M. Bradshaw. The dynamics of trust in cyberdomains. IEEE Intell. Syst. 24(6), 5–11 (2009)Google Scholar
  14. 14.
    R.C. Arkin, P. Ulam, A.R. Wagner, Moral decision making in autonomous systems: enforcement, moral emotions, dignity, trust, and deception. Proc. IEEE 100(3), 571–589 (2012)Google Scholar
  15. 15.
    A.B. Can, B. Bhargava. Sort: a self-organizing trust model for peer-to-peer systems. IEEE Trans. Dependable Secure Comput. 10(1), 14–27 (2013)Google Scholar
  16. 16.
    X. Li, F. Zhou, X. Yang, Scalable feedback aggregating (SFA) overlay for large-scale P2P trust management. IEEE Trans. Parallel Distrib. Syst. 23(10), 1944–1957 (2012)Google Scholar
  17. 17.
    M. Omar, Y. Challal, A. Bouabdallah, Certification-based trust models in mobile ad hoc networks: a survey and taxonomy. J. Network Comput. Appl. 35(1), 268–286 (2012)Google Scholar
  18. 18.
    Y. Han, Z. Shen, C. Miao, C. Leung, D. Niyato. A survey of trust and reputation management systems in wireless communications. Proc. IEEE 98(10), 1755–1772 (2010)Google Scholar
  19. 19.
    R. Akbani, T. Korkmaz, G.V. Raju, Emltrust: an enhanced machine learning based reputation system for MANETs. Ad Hoc Networks 10(3), 435–457 (2012)Google Scholar
  20. 20.
    G.-B. Huang, Q.-Y. Zhu, C.-K. Siew. Extreme learning machine: a new learning scheme of feedforward neural networks, in IEEE International Conference on Neural Networks—Conference Proceedings, vol. 2, pp. 985–990 (2004). (Cited By (since 1996), 113)Google Scholar
  21. 21.
    G.-B. Huang, Q.-Y. Zhu, C.-K. Siew, Extreme learning machine: theory and applications. Neurocomputing 70, 489–501 (2006)Google Scholar
  22. 22.
    P. Massa, P. Avesani, Controversial users demand local trust metrics: an experimental study on epinions.com community, in Proceedings of the National Conference on Artificial Intelligence, vol. 1, pp. 121–126 (2005). (Cited By (since 1996), 36)Google Scholar
  23. 23.
    P. Massa, P. Avesani, Trust metrics on controversial users: balancing between tyranny of the majority and echo chambers. Int. J. Semant. Web Inf. Syst. 3(1), 39–64 (2007). (Cited By (since 1996), 26)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Computational Intelligence GroupUniversity of the Basque CountryUPV/EHUSpain

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