Exploring A Trust Based Recommendation Approach for Videos in Online Social Network

Journal of Signal Processing Systems

Volumn 86, Issue 2-3, 2017, Pages 207-219

  Cui, Laizhong ^a   Sun, Lili ^a   Fu, Xianghua ^a   Lu, Nan ^a   Zhang, Guanjing ^b  

^a SHENZHEN UNIVERSITY   (China)

^b E Techco Information Technologies CoLtd   (China)

Author keywords

Online video; Social network; Trust; User recommendation; Video recommendation

Indexed keywords

ONLINE SYSTEMS;

INTERACTION INFORMATION; ON-LINE SOCIAL NETWORKS; ONLINE VIDEO; RECOMMENDATION ALGORITHMS; TRUST; TRUST-BASED RECOMMENDATIONS; USER RECOMMENDATIONS; VIDEO RECOMMENDATION;

SOCIAL NETWORKING (ONLINE);

EID: 84959540775     PISSN: 19398018     EISSN: 19398115     Source Type: Journal    
DOI: 10.1007/s11265-016-1116-7     Document Type: Article

References (22)

1. Li, J., Qiu, M., Ming, Z., Quan, G., Qin, X., & Gu, Z. (2012). Online optimization for scheduling preemptable tasks on IaaS cloud systems. Journal of Parallel and Distributed Compututing (JPDC), 72(5), 666–677.
2. Qiu, M., Gao, W., Chen, M., Niu, J., & Zhang, L. (2011). Energy efficient security algorithm for power grid wide area monitoring system. IEEE Transactions on Smart Grid, 2(4), 715–723.
3. Qiu, M., & Sha, E.H.-M. (2009). Cost minimization while satisfying hard/soft timing constraints for heterogeneous embedded systems. ACM Transactions on Design Automation of Electronic Systems (TODAES), 14(2), 25:1–25:30. Article 25.
4. Niu, J., Gao, Y., Qiu, M., & Ming, Z. (2012). Selecting proper wireless network interfaces for user experience enhancement with guaranteed probability. Journal of Parallel and Distributed Computing (JPDC), 72 (12), 1565–1575.
5. Leony, D., Pardo, A., Parada, H.A.G., & Kloos, C.D. (2012). A cloud-based architecture for an affective recommender system of learning resources. In Proceedings of the 1st international workshop on cloud education environments (WCLOUD ’12) (pp. 41–46).
6. Mo, Y., Chen, J., Xie, X., Luo, C., & Yang, L.T. (2014). Cloud-Based Mobile multimedia recommendation system with user behavior information. IEEE Systems Journal, 8(1), 184–193.
7. Meikang, Qiu, Zhong, Ming, Jiayin, Li, Keke, Gai, & Ziliang, Zong (2015). Phase-Change Memory Optimization for Green Cloud with Genetic Algorithm. IEEE Transactions on Computers, 64(12), 3528–3540.
8. Qiu, M., Chen, Z., Ming, Z., Qin, X., & Niu, J. (2014). Energy-aware data allocation with hybrid memory for mobile cloud systems. IEEE Systems Journal, PP(99), 1–10.
9. Park, J., Lee, S.-J., Lee, S.-J., Kim, K., Chung, B.-S., & Lee, Y.-K. (2011). Online video recommendation through tag-cloud aggregation. IEEE MultiMedia, 18(1), 78–87.
10. Li, Z., Lin, J., Salamatian, K., & Xie, G. (2013). Social connections in user-generated content video systems: Analysis and recommendation. IEEE Transactions on Network and Service Management, 10(1), 70–83.
11. Xing, X., Zhang, W., Jia, Z., & Zhang, X. (2012). Trust-based social item recommendation: A case study. In Proceedings of 2012 2nd international conference on computer science and network technology (ICCSNT) (pp. 1050–1053).
12. Jin, J., & Chen, Q. (2012). A trust-based Top-K recommender system using social tagging network. In Proceedings of 2012 9th international conference on fuzzy systems and knowledge discovery (FSKD) (pp. 1270–1274).
13. Lumbreras, A., & Gavalda, R. (2012). Applying trust metrics based on user interactions to recommendation in social networks. In Proceedings of 2012 IEEE/ACM international conference on advances in social networks analysis and mining (ASONAM) (pp. 1159–1164).
14. Tang, M., Xu, Y., Liu, J., Zheng, Z., & Liu, X. (2013). Trust-aware service recommendation via exploiting social networks. In Proceedings of 2013 IEEE international conference on services computing (SCC) (pp. 376–383).
15. Davidson, J., Liebald, B., Liu, J., Nandy, P., Van Vleet, T., Gargi, U., Gupta, S., He, Y., Lambert, M., Livingston, B., & Sampath, D. (2010). The YouTube video recommendation system. In Proceedings of 2010 4th ACM conference on recommender systems (recsys) (pp. 293–296).
16. Ma, X., Wang, H., Li, H., Liu, J., & Jiang, H. (2014). Exploring sharing patterns for video recommendation on YouTube-like social media. Multimedia Systems, 20(6), 675– 691.
17. De Campos, L.M., Fernndez-luna, J.M., Huete, J.F., & Rueda-Morales, M.A. (2010). Combining content-based and collaborative recommendations: A hybrid approach based on Bayesian networks. International Journal of Approximate Reasoning, 51(7), 785–799.
18. De Pessemier, T., Coppens, S., Geebelen, K., Vleugels, C., Bannier, S., Mannens, E., Vanhecke, K., & Martens, L. (2012). Collaborative recommendations with content-based filters for cultural activities via a scalable event distribution platform. Multimedia Tools Applications, 58(1), 167–213.
19. Yoshida, T., Irie, G., Arai, H., & Taniguchi, Y. (2013). Towards semantic and affective content-based video recommendation. In Proceedings of 2013 IEEE international conference on multimedia and expo workshops (ICMEW) (pp. 1–6).
20. Shin, S., Jang, S.-J., & Lee, S.-p. (2011). The User-Group based recommendation for the diverse multimedia contents in the social network environments. In Proceedings of 2011 IEEE ninth international conference on proceedings of dependable, autonomic and secure computing (DASC) (pp. 202–206).
21. Yoshida, T., Irie, G., Satou, T., Kojima, A., & Higashino, S. (2012). Improving item recommendation based on social tag rangking. In Proceedings of 2012 18th international conference on multimedia modeling (pp. 161–172).
22. Liu, Q., & Li, S. (2002). Word Semantic Similarity Computation based on HowNet. In Proceedings of the 3rd chinese lexical semantic workshop (CLSW2002) (pp. 59–76).