Advertisement

An Efficient Method to Find the Optimal Social Trust Path in Contextual Social Graphs

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9050)

Abstract

Online Social Networks (OSN) have been used as platforms for many emerging applications, where trust is a critical factor for participants’ decision making. In order to evaluate the trustworthiness between two unknown participants, we need to perform trust inference along the social trust paths formed by the interactions among the intermediate participants. However, there are usually a large number of social trust paths between two participants. Thus, a challenging problem is how to effectively and efficiently find the optimal social trust path that can yield the most trustworthy evaluation result based on the requirements of participants. In this paper, the core problem of finding the optimal social trust path with multiple constraints of social contexts is modelled as the classical NP-Complete Multi-Constrained Optimal Path (MCOP) selection problem. To make this problem practically solvable, we propose an efficient and effective approximation algorithm, called T-MONTE-K, by combining Monte Carlo method and our optimised search strategies. Lastly we conduct extensive experiments based on a real-world OSN dataset and the results demonstrate that the proposed T-MONTE-K algorithm can outperform state-of-the-art MONTE_K algorithm significantly.

Keywords

Neighboring Node Online Social Network Trust Evaluation Trust Propagation Trust Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Hang, C., Wang, Y., Singh, M.: Operators for propagating trust and their evaluation in social networks. In: AAMAS 2009, pp. 1025–1032 (2009)Google Scholar
  2. 2.
    Liu, G., Wang, Y., Orgun, M.A.: Optimal social trust path selection in complex social networks. In: AAAI 2010, pp. 1397–1398 (2010)Google Scholar
  3. 3.
    Adler, P.S.: Market, hierarchy, and trust: The knowledge economy and the future of capitalism. Organization Science 12(12), 215–234 (2001)CrossRefGoogle Scholar
  4. 4.
    Ashri, R., Ramchurn, S., Sabater, J., Luck, M., Jennings, N.: Trust evaluation through relationship analysis. In: AAMAS 2005, pp. 1005–1011Google Scholar
  5. 5.
    Brass, D.J.: A Socal Network Prespective On Industral/organizational psychology. Industrial/Organizational Handbook (2009)Google Scholar
  6. 6.
    Dalton, M.: Men Who Manage. Wiley, New York (1959)Google Scholar
  7. 7.
    Golbeck, J., Hendler, J.: Inferring trust relationships in web-based social networks. ACM Transactions on Internet Technology 6(4), 497–529 (2006)CrossRefGoogle Scholar
  8. 8.
    Kunegis, J., Lommatzsch, A., Bauckhang, C.: The slashdot zoo: Mining a social network with negative edges. In: WWW 2009, pp. 741–750Google Scholar
  9. 9.
    Baase, S., Gelder, A.: Computer Algorithms Introduction to Design and Analysis. Addision WesleyGoogle Scholar
  10. 10.
    Christianson, B., Harbison, W.S.: Why isn’t trust transitivie? In: Lomas, M. (ed.) Security Protocols 1996. LNCS, vol. 1189, pp. 171–176. Springer, Heidelberg (1997) CrossRefGoogle Scholar
  11. 11.
    Mansell, R., Collins, B.: Trust and Crime in Information Societies. Edward Elgar Publishing (2005)Google Scholar
  12. 12.
    Lin, C., Cao, N., Liu, S., Papadimitriou, S., Sun, J., Yan, X.: Smallblue: Social network analysis for expertise search and collective intelligence. In: ICDE 2009, pp. 1483–1486 (2009)Google Scholar
  13. 13.
    Miller, R., Perlman, D., Brehm, S.: Intimate Relationships, 4th edn. McGraw-Hill College (2007)Google Scholar
  14. 14.
    Liu, G., Wang, Y., Orgun, M., Lim, E.P.: A heuristic algorithm for trust-oriented service provider selection in complex social networks. In: SCC, pp. 130–137 (2010)Google Scholar
  15. 15.
    Liu, G., Wang, Y., Orgun, M.A.: Finding k optimal social trust paths for the selection of trustworthy service providers in complex social networks. In: ICWS 2011, pp. 41–48Google Scholar
  16. 16.
    Liu, G., Wang, Y., Orgun, M.A., Lim, E.P.: Finding the optimal social trust path for the selection of trustworthy service providers in complex social networks. IEEE Transactions on Services Computing (TSC) (2011)Google Scholar
  17. 17.
    Liu, G., Wang, Y., Wong, D.: Multiple qot constrained social trust path selection in complex social networks. In: TrustCom 2012Google Scholar
  18. 18.
    Sakaki, T., Okazaki, M., Matsuo, Y.: Tweet analysis for real-time event detection and earthquake reporting system development. IEEE Transactions on Knowledge and Data Engineering 25(4), 919–931 (2013)CrossRefGoogle Scholar
  19. 19.
    Shin, Y., Lim, J., Park, J.: Joint optimization of index freshness and coverage in real-time search engines. IEEE Transactions on Knowledge and Data Engineering 24(12), 2203–2217 (2012)CrossRefGoogle Scholar
  20. 20.
    Gentle, J., Hardle, W., Mori, Y.: Handbook of Computational Statistics. Springer (2004)Google Scholar
  21. 21.
    Wang, G., Wu, J.: Multi-dimensional evidence-based trust management with multi-trusted paths. Future Generation Computer Systems 17, 529–538 (2011)CrossRefGoogle Scholar
  22. 22.
    Liu, G., Wang, Y., Orgun, M.A.: Trust transitivity in complex social networks. In: AAAI 2011, pp. 1222–1229Google Scholar
  23. 23.
    Mccallum, A., Wang, X., Corrada-Emmanuel, A.: Topic and role discovery in social networks with experiments on Enron and academic email. Journal of Artificial Intelligence Research 30(1), 249–272 (2007)Google Scholar
  24. 24.
    Tang, J., Zhang, J., Yan, L., Li, J., Zhang, L., Su, Z.: Arnetminer: Extraction and mining of academic social networks. In: KDD 2008, pp. 990–998 (2008)Google Scholar
  25. 25.
    Berger, P., Luckmann, T.: The Social Construction of Reality: A Treatise in the Sociology of Knowledge. Anchor Books (1966)Google Scholar
  26. 26.
    Korkmaz, T., Krunz, M.: Multi-constrained optimal path selection. In: INFOCOM 2001, pp. 834–843Google Scholar
  27. 27.
    Morton, D., Popova, E.: Monte-carlo simulation for stochastic optimization. Encyclopedia of Optimization, pp. 2337–2345 (2009)Google Scholar
  28. 28.
    Mislove, A., Marcon, M., Gummadi, K., Druschel, P., Bhattacharjee, B.: Measurement and analysis of online social networks. In: ACM IMC 2007, pp. 29–42 (2007)Google Scholar
  29. 29.
    Chia, P., Pitsilis, G.: Exploring the use of explicit trust link for filtering recommenders: A study on epinions.com. Journal of Information Processing 19, 332–344 (2011)CrossRefGoogle Scholar
  30. 30.
    Chua, F., Lim, E.P.: Trust network inference for online rating data using generative models. In: KDD 2010, pp. 889–898Google Scholar
  31. 31.
    Lo, D., Surian, D., Zhang, K., Lim, E.P.: Mining direct antagonistic communities in explicit trust networks. In: CIKM 2011, pp. 1013–1018Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.School of Computer ScienceSoochow UniversitySuzhouChina
  2. 2.Collaborative Innovation Center of Novel Software Technology and IndustrializationJiangsuChina
  3. 3.School of Information Technology and Electrical EngineeringThe University of QueenslandBrisbaneAustralia
  4. 4.School of Computer Science and Information TechnologyRMIT UniversityMelbourneAustralia

Personalised recommendations