Refine social relations and differentiate the same friends’ influence in recommender system

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 9468, Issue , 2015, Pages 504-514

  Zhai, Haitao ^a   Li, Jing ^a  

^a UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

Author keywords

PMF; Recommender system; Refine friends; Social rating network

Indexed keywords

ARTIFICIAL INTELLIGENCE; FACTORIZATION; FILTRATION; LEARNING SYSTEMS;

PMF; PROBABILISTIC MATRIX FACTORIZATIONS; PUBLIC DATA; SOCIAL RATINGS; SOCIAL RELATIONS;

RECOMMENDER SYSTEMS;

EID: 84955271113     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-26832-3_47     Document Type: Conference Paper

References (15)

1. Qian, X., Feng, H., Zhao, G., Mei, T.: Personalized recommendation combining user interest and social circle. IEEE Trans. Knowl. Data Eng. 26(7), 1763-1777 (2014)
2. Mnih, A., Salakhutdinov, R.: Probabilistic matrix factorization. In: Advances in Neural Information Processing Systems, pp. 1257-1264 (2007)
3. Yang, X., Guo, Y., Liu, Y.: Bayesian-inference-based recommendation in online social networks. IEEE Trans. Parallel Distrib. Syst. 24(4), 642-651 (2013)
4. Ma, H., Zhou, D., Liu, C., Lyu, M.R., King, I.: Recommender systems with social regularization. In: Proceedings of the Fourth ACM International Conference on Web Search and Data Mining. ACM, pp. 287-296 (2011)
5. Wang, D., Ma, J., Lian, T., Guo, L.: Recommendation based on weighted social trusts and item relationships. In: Proceedings of the 29th Annual ACM Symposium on Applied Computing. ACM, pp. 254-259 (2014)
6. Wang, Z., Yang, Y., Hu, Q., He, L.: An empirical study of personal factors and social effects on rating prediction. In: Cao, T., Lim, E.-P., Zhou, Z.-H., Ho, T.-B., Cheung, D., Motoda, H. (eds.) PAKDD 2015. LNCS, vol. 9077, pp. 747-758. Springer, Heidelberg (2015)
7. Tuzhilin, A.: Towards the next generation of recommender systems. In: Proceedings of the 1st International Conference on E-Business Intelligence (ICEBI2010), Atlantis Press (2010)
8. Jin, R., Chai, J.Y., Si, L.: An automatic weighting scheme for collaborative filtering. In: Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, pp. 337-344 (2004)
9. Linden, G., Smith, B., York, J.: Amazon. com recommendations: item-to-item collaborative filtering. Internet Comput. 7(1), 76-80 (2003)
10. OConnor, M., Herlocker, J.: Clustering items for collaborative filtering. In: Proceedings of the ACM SIGIR Workshop on Recommender Systems, vol. 128, Citeseer (1999)
11. Hofmann, T.: Latent semantic models for collaborative filtering. ACM Trans. Inf. Syst. (TOIS) 22(1), 89-115 (2004)
12. Jamali, M., Ester, M.: A matrix factorization technique with trust propagation for recommendation in social networks. In: Proceedings of the Fourth ACM Conference on Recommender Systems. ACM, pp. 135-142 (2010)
13. Yang, X., Steck, H., Liu, Y.: Circle-based recommendation in online social networks. In: Proceedings of the 18th ACM SIGKDD International Conference On Knowledge Discovery And Data Mining. ACM, pp. 1267-1275 (2012)
14. Zhang, X., Cheng, J., Yuan, T., Niu, B., Lu, H.: Toprec: domain-specific recommendation through community topic mining in social network. In: Proceedings of the 22nd International Conference on World Wide Web, International World Wide Web Conferences Steering Committee, pp. 1501-1510 (2013)
15. http://smiles.xjtu.edu.cn