HYBRIDISING COLLABORATIVE FILTERING AND TRUST-AWARE RECOMMENDER SYSTEMS

Charif Haydar, Anne Boyer, Azim Roussanaly

Abstract

Recommender systems (RS) aim to predict items that users would appreciate, over a list of items. In evaluation of recommender systems, two issues can be defined: accuracy of prediction which implies the satisfaction of the user, and coverage which implies the percentage of satisfied users. Collaborative filtering (CF) is the master approach in this domain, but still has some weaknesses especially about coverage. Trust-aware approach is today another promising approach in RS within social environments, whose prediction exceeds the quality of (CF). In this paper we propose several strategies to hybridize both approaches in order to improve prediction accuracy and coverage.

References

  1. Abdul-Rahman, A. (2004). A Framework for Decentralised Trust Reasoning. phD thesis. PhD thesis, Computer Sceince, University College London.
  2. Baltrunas, R. (2007). Dynamic item weighting and selection for collaborative filtering. In Web mining 2.0 Workshop.
  3. Basu, C., Hirsh, H., and Cohen, W. (1998). Recommendation as classification: using social and content-based information in recommendation. In Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence.
  4. Breese, J. S., Heckerman, D., and Kadie, C. (1998). Empirical analysis of predictive algorithm for collaborative filtering. In Proceedings of the 14 th Conference on Uncertainty in Artificial Intelligence, pages 43-52.
  5. Burke, R. (2007). Hybrid web recommender systems. In Brusilovsky, P., Kobsa, A., and Nejdl, W., editors, The adaptive web, pages 377-408. Springer-Verlag, Berlin, Heidelberg.
  6. Burke, R., Mobasher, B., Zabicki, R., and Bhaumik, R. (2005). Identifying attack models for secure recommendation. In in Beyond Personalization: A Workshop on the Next Generation of Recommender Systems.
  7. Golbeck, J. (2005). Personalizing applications through integration of inferred trust values in semantic web-based social networks.
  8. Golbeck, J. and Hendler, J. (2006). FilmTrust: movie recommendations using trust in web-based social networks. In Consumer Communications and Networking Conference, 2006. CCNC 2006. 3rd IEEE.
  9. Herlocker, J. L., Konstan, J. A., and Riedl, J. (2000). Explaining collaborative filtering recommendations. Proceedings of the 2000 ACM conference on Computer supported cooperative work CSCW 00.
  10. Herlocker, J. L., Konstan, J. A., Terveen, L. G., John, and Riedl, T. (2004). Evaluating collaborative filtering recommender systems. ACM Transactions on Information Systems, 22:5-53.
  11. Kruknow, K. (2006). Towards of trust for the global Ubiquitous Computer. PhD thisis. PhD thesis, University of Aartus.
  12. Kuter, U. and Golbeck, J. (2010). Using probabilistic confidence models for trust inference in web-based social networks. ACM Trans. Internet Technol.
  13. Lee, D. H. and Brusilovsky, P. (2009). Does trust influence information similarity?
  14. Maltz, D. and Ehrlich, K. (1995). Pointing the way: active collaborative filtering. In Proceedings of the SIGCHI conference on Human factors in computing systems.
  15. Massa, A. (2006). Trust-aware bootstrapping of recommender systems. In ECAI Workshop on Recommender Systems.
  16. Massa, P. and Avesani, P. (2004). Trust-aware collaborative filtering for recommender systems. In In Proc. of Federated Int. Conference On The Move to Meaningful Internet: CoopIS, DOA, ODBASE, pages 492-508.
  17. Massa, P. and Bhattacharjee, B. (2004). Using trust in recommender systems: An experimental analysis. In iTrust'04, pages 221-235.
  18. Mobasher, B., Burke, R., Bhaumik, R., and Williams, C. (2007). Toward trustworthy recommender systems: An analysis of attack models and algorithm robustness. ACM Transactions on Internet Technology.
  19. Mui, L. (2002). Computional Models of Trust and Reputation: Agents, Evolutionary Games,and Social Networks. PhD thesis. PhD thesis, Massechusetts Institute of Technology.
  20. Resnick, P., Iacovou, N., Sushak, M., Bergstrom, P., and Riedl, J. (1994). Grouplens: An open architecture for collaborative filtering of netnews. In 1994 ACM Conference on Computer Supported Collaborative Work Conference.
  21. Resnick, P. and Varian, H. R. (1997). Recommender systems. Commun. ACM, 40(3):56-58.
  22. Shin, H., Kim, N. Y., Kim, E. Y., and Lee, M. (2008). Behaviors-based user profiling and classificationbased content rating for personalized digital tv. In Consumer Electronics, 2008. ICCE 2008. Digest of Technical Papers. International Conference on.
  23. Ziegler, C.-N. and Lausen, G. (2004a). Analyzing correlation between trust and user similarity in online communities. In Proceedings of Second International Conference on Trust Management, pages 251-265. Springer-Verlag.
  24. Ziegler, C.-N. and Lausen, G. (2004b). Spreading activation models for trust propagation. In Proceedings of the 2004 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'04).
Download


Paper Citation


in Harvard Style

Haydar C., Boyer A. and Roussanaly A. (2012). HYBRIDISING COLLABORATIVE FILTERING AND TRUST-AWARE RECOMMENDER SYSTEMS . In Proceedings of the 8th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-8565-08-2, pages 695-700. DOI: 10.5220/0003937406950700


in Bibtex Style

@conference{webist12,
author={Charif Haydar and Anne Boyer and Azim Roussanaly},
title={HYBRIDISING COLLABORATIVE FILTERING AND TRUST-AWARE RECOMMENDER SYSTEMS},
booktitle={Proceedings of the 8th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},
year={2012},
pages={695-700},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003937406950700},
isbn={978-989-8565-08-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - HYBRIDISING COLLABORATIVE FILTERING AND TRUST-AWARE RECOMMENDER SYSTEMS
SN - 978-989-8565-08-2
AU - Haydar C.
AU - Boyer A.
AU - Roussanaly A.
PY - 2012
SP - 695
EP - 700
DO - 10.5220/0003937406950700