Bayesian-inference based recommendation in online social networks

Proceedings - IEEE INFOCOM

Volumn , Issue , 2011, Pages 551-555

  Yang, Xiwang ^a   Guo, Yang ^b   Liu, Yong ^a  

^a POLYTECHNIC UNIVERSITY   (United States)

^b LUCENT TECHNOLOGIES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CONDITIONAL PROBABILITIES; DATA SETS; DISTRIBUTED PROTOCOLS; MOVIE RATINGS; ONLINE SOCIAL NETWORKS; PERSONALIZED RECOMMENDATION; QUERY RESPONSE; SOCIAL NETWORKS;

ALGORITHMS; BAYESIAN NETWORKS; INFERENCE ENGINES; MOTION PICTURES; QUERY PROCESSING; RATING;

SOCIAL NETWORKING (ONLINE);

EID: 79960867244     PISSN: 0743166X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/INFCOM.2011.5935224     Document Type: Conference Paper

References (16)

1. ADOMAVICIUS, G., AND TUZHILIN, A. Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering 17, 6 (June 2005).
2. ANSARI, A., ESSEGAIER, S., AND KOHLI, R. Internet recommendations systems. In Journal of Marketing Research (August 2000), pp. 363-375.
3. BREESE, J. S., HECKERMAN, D., AND KADIE, C. Empirical analysis of predictive algorithms for collaborative filtering. Morgan Kaufmann, pp. 43-52.
4. CHIEN, Y.-H., AND GEORGE, E. A bayesian model for collaborative filtering. In Proceedings of Seventh International Workshop Artificial Intelligence and Statistics (1999).
5. DUBOIS, T., GOLBECK, J., KLEINT, J., AND SRINIVASAN, A. Improving recommendation accuracy by clustering social neworks with trust. In Proceedings of the ACM RecSys 2009 Workshop on Recommender Systems and the Social Web (October 2009).
6. FACEBOOK. http://www.facebook.com.
7. GOLBECK, J., AND HENDLER, J. Filmtrust: Movie recommendations using trust in web-based social networks. In Proceedings of the IEEE Consumer Communications and Networking Conference (January 2006).
8. GROUPLENS RESEARCH. MovieLens Data Sets, 2010. http://www.grouplens.org/ node/73#attachments.
9. HERLOCKER, J., KONSTAN, J., TERVEEN, L., AND RIDEL, J. Evaluating collaborative filtering recommender systems. ACM Transactions on Information Systems (TOIS) 22, 1 (January 2004).
10. MASSA, P., AND AVESANI, P. Controversial users demand local trust metrics: an experimental study on epinions.com community. In Proceedsings of the 25th American Association for Artificial Intelligence Conference (2005).
11. MCPHERSON, M., SMITH-LOVIN, L., AND COOK, J. Birds of a feather: Homophily in social networks. Annual Review of Sociology 27 (2001).
12. NETFLIXPRIZE. http://www.netflixprize.com/.
13. TWITTER. http://twitter.com.
14. YOUTUBE. http://www.youtube.com.
15. ZIEGLER, C.-N., AND GOLBECK, J. Investigating interactions of trust and interest similarity. Decis. Support Syst. 43, 2 (2007), 460-475.
16. ZIEGLER, C.-N., AND LAUSEN, G. Analyzing correlation between trust and user similarity in online communities. In Proceedings of Second International Conference on Trust Management (2004), Springer-Verlag, pp. 251-265.