Skip to main content
SpringerLink
Log in

Heterogeneity, quality, and reputation in an adaptive recommendation model

  • Published:
The European Physical Journal B Aims and scope Submit manuscript

Abstract.

Recommender systems help people cope with the problem of information overload. A recently proposed adaptive news recommender model [M. Medo, Y.-C. Zhang, T. Zhou, Europhys. Lett. 88, 38005 (2009)] is based on epidemic-like spreading of news in a social network. By means of agent-based simulations we study a “good get richer” feature of the model and determine which attributes are necessary for a user to play a leading role in the network. We further investigate the filtering efficiency of the model as well as its robustness against malicious and spamming behaviour. We show that incorporating user reputation in the recommendation process can substantially improve the outcome.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. M. Medo, Y.-C. Zhang, T. Zhou, Europhys. Lett. 88, 38005 (2009)

    Article  ADS  Google Scholar 

  2. M.H. Goldhaber, First Monday 2 (1997)

  3. B.A. Huberman, Council on Library and Information Resources (USA, 2008)

  4. P. Resnick, H.R. Varian, Commun. ACM 40, 56 (1997)

    Article  Google Scholar 

  5. J.L. Herlocker, J.A. Konstan, L.G. Terveen, J.T. Riedl, ACM Trans. Inf. Syst. 22, 5 (2004)

    Article  Google Scholar 

  6. G. Adomavicius, A. Tuzhilin, IEEE Trans. Knowl. Data Eng. 17, 734 (2005)

    Article  Google Scholar 

  7. G. Linden, B. Smith, J. York, IEEE Internet Computing 7, 76 (2003)

    Article  Google Scholar 

  8. J. Breese, D. Heckerman, C. Kadie, In Proc. of the 14th Conf. on Uncertainty in Artificial Intelligence (1998)

  9. T. Hofmann, ACM Trans. Inf. Syst. 22, 89 (2004)

    Article  Google Scholar 

  10. S. Maslov, Y.-C. Zhang, Phys. Rev. Lett. 87, 248701 (2001)

    Article  ADS  Google Scholar 

  11. R. Sinha, K. Swearingen, Proc. DELOS-NSF Workshop on Personalization and Recommender Systems in Digital Libraries (2001)

  12. J. Golbeck, Science 321, 1640 (2008)

    Article  Google Scholar 

  13. T. Zhou, Z.-Q. Fu, B.-H. Wang, Prog. Nat. Sci. 16, 452 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  14. Y. Moreno, M. Nekovee, A.F. Pacheco, Phys. Rev. E 69, 066130 (2004)

    Article  ADS  Google Scholar 

  15. G. Caldarelli, Scale-Free Networks: Complex Webs in Nature and Technology (Oxford Press, New York, 2007)

  16. G. Caldarelli, A. Capocci, P. De Los Rios, P.A. Muñoz, Phys. Rev. Lett. 89, 258702 (2002)

    Article  ADS  Google Scholar 

  17. P. Resnick, K. Kuwabara, R. Zeckhauser, E. Friedman, Commun. ACM 43, 12 (2000)

    Article  Google Scholar 

  18. F. Wu, B.A. Huberman, Proc. Natl. Acad. Sci. USA 104, 45 (2007)

    Google Scholar 

  19. T. Gross, B. Blasius, J. R. Soc. Interface 5, 259 (2008)

    Article  Google Scholar 

  20. R. Guha, R. Kumar, P. Raghavan, A. Tomkins, WWW’04 Proceedings of the 13th International World Wide Web conference (ACM, 2004)

  21. J. Leskovec, D.P. Huttenlocher, J.M. Kleinberg, WWW10: Proceedings of the 19th International World Wide Web Conference (ACM, 2010)

  22. T. Zhou, H.A.T. Kiet, B.J. Kim, B.-H. Wang, P. Holme, Europhys. Lett. 82, 28002 (2008)

    Article  ADS  Google Scholar 

  23. P. Cano, O. Celma, M. Koppenberger, J.M. Buldú, Chaos 16, 013107 (2006)

    Article  ADS  Google Scholar 

  24. J. Ito, K. Kaneko, Phys. Rev. E 67, 046226 (2003)

    Article  ADS  Google Scholar 

  25. J. Lorenz, S. Battiston, F. Schweitzer, EPJ B 71, 441 (2009)

    MATH  ADS  MathSciNet  Google Scholar 

  26. A. Jøsang, R. Ismail, C. Boyd, Decis. Support Syst. 43, 618 (2007)

    Article  Google Scholar 

  27. L. Freeman, Soc. Networks 1, 215 (1979)

    Article  Google Scholar 

  28. R. Kumar, J. Novak, A. Tomkins, Proc. 12th ACM SIGKDD (2006)

  29. J.H. Miller, S.E. Page, Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton University Press, 2007)

Download references

Author information

Authors and Affiliations

  1. Physics Department, University of Fribourg, 1700, Fribourg, Switzerland

    G. Cimini, M. Medo, T. Zhou, D. Wei & Y.-C. Zhang

  2. Web Sciences Center, University of Electronic Science and Technology of China, Chengdu, 610054, P.R. China

    T. Zhou

  3. Department of Modern Physics, University of Science and Technology of China, Hefei, 230026, P.R. China

    T. Zhou

Authors
  1. G. Cimini
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. Medo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. T. Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. D. Wei
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Y.-C. Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to G. Cimini.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Cimini, G., Medo, M., Zhou, T. et al. Heterogeneity, quality, and reputation in an adaptive recommendation model. Eur. Phys. J. B 80, 201–208 (2011). https://doi.org/10.1140/epjb/e2010-10716-5

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1140/epjb/e2010-10716-5

Keywords

Search

Navigation