Personalized video recommendation based on viewing history with the study on YouTube

ACM International Conference Proceeding Series

Volumn , Issue , 2012, Pages 161-165

  Zhao, Xiaojian ^a   Luan, Huanbo ^b   Cai, Junjie ^c   Yuan, Jin ^b   Chen, Xiaoming ^a   Li, Zhoujun ^a  

^a BEIHANG UNIVERSITY   (China)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^c One UTSA Circle   (United States)

Author keywords

Multimodal similarity; Personalized video recommendation; Tag set; Viewing history

Indexed keywords

INTERNET DELIVERY; MULTI-MODAL; PERSONALIZED VIDEO; TAG SET; VIDEO CONTENTS; YOUTUBE;

COMPUTER APPLICATIONS;

INTERNET;

EID: 84869039735     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2382336.2382382     Document Type: Conference Paper

References (28)

1. Encyclopedia. http://en.wikipedia.org/wiki/YouTube/.
2. G. Adomavicius and A. Tuzhilin. 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):734-749, 2005.
3. S. Boll. Multitube-where web 2.0 and multimedia could meet. IEEE Multimedia, 14(1):9-13, 2007.
4. R. Burke. Hybrid web recommender systems. Lecture Notes in Computer Science, pages 377-408, 2007.
5. R. Cilibrasi and P. Vitanyi. The google similarity distance. IEEE Transactions on Knowledge and Data Engineering, pages 370-383, 2007.
6. M. Deshpande and G. Karypis. Item-based top-n recommendation algorithms. ACM Transactions on Information System, 22:143-177, 2004.
7. M. Gibas, G. Canahuate, and H. Ferhatosmanoglu. Online index recommendations for high-dimensional databases using query workloads. IEEE Transactions on Knowledge and Data Engineering, pages 246-260, 2008.
8. J. Herlocker, J. Konstan, L. Terveen, and J. Riedl. Evaluating collaborative filtering recommender systems. ACM Transactions on Information Systems (TOIS), 22(1):5-53, 2004.
9. R. Hong, M. Wang, M. Xu, S. Yan, and T. Chua. Dynamic captioning: video accessibility enhancement for hearing impairment. In Proceedings of the ACM International Conference on Multimedia, pages 421-430, 2010.
10. X. Hu and H. Liu. Social status and role analysis of palin's email network. In Proceedings of the 21st international conference companion on World Wide Web, WWW '12 Companion, pages 531-532, 2012.
11. X. Hu and H. Liu. Text analytics in social media. Mining Text Data, pages 385-414, 2012.
12. X. Hu, N. Sun, C. Zhang, and T. Chua. Exploiting internal and external semantics for the clustering of short texts using world knowledge. In Proceeding of the 18th ACM conference on Information and knowledge management, pages 919-928. ACM, 2009.
13. X. Hu, L. Tang, and H. Liu. Enhancing accessibility of microblogging messages using semantic knowledge. In Proceedings of the 20th ACM international conference on Information and knowledge management, pages 2465-2468. ACM, 2011.
14. G. Irie, K. Hidaka, T. Satou, T. Yamasaki, and K. Aizawa. A degree-of-edit ranking for consumer generated video retrieval. pages 1242 -1245. IEEE International Conference on Multimedia and Expo, 2009.
15. T. Mei, B. Yang, X. Hua, and S. Li. Contextual video recommendation by multimodal relevance and user feedback. ACM Transactions on Information Systems (TOIS), 29(2):10, 2011.
16. T. Mei, B. Yang, X.-S. Hua, L. Yang, S.-Q. Yang, and S. Li. Videoreach: an online video recommendation system. In Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, pages 767-768, 2007.
17. G. Öztürk and N. Kesim Cicekli. A hybrid video recommendation system using a graph-based algorithm. Modern Approaches in Applied Intelligence, pages 406-415, 2011.
18. J. Park, S. Lee, K. Kim, B. Chung, and Y. Lee. An online video recommendation framework using view based tag cloud aggregation. Multimedia, IEEE, 18(99):78-87, 2011.
19. P. Resnick, K. Kuwabara, R. Zeckhauser, and E. Friedman. Reputation systems. Communications of the ACM, 43(12):45-48, 2000.
20. B. Sarwar, G. Karypis, J. Konstan, and J. Reidl. Item-based collaborative filtering recommendation algorithms. In Proceedings of the 10th international conference on World Wide Web, pages 285-295, 2001.
21. M. Wang, X. Hua, R. Hong, J. Tang, G. Qi, and Y. Song. Unified video annotation via multigraph learning. IEEE Transactions on Circuits and Systems for Video Technology, 19(5):733-746, 2009.
22. M. Wang, X. Hua, J. Tang, and R. Hong. Beyond distance measurement: constructing neighborhood similarity for video annotation. IEEE Transactions on Multimedia, 11(3):465-476, 2009.
23. M. Wang, K. Yang, X.-S. Hua, and H.-J. Zhang. Towards a relevant and diverse search of social images. IEEE Transactions on Multimedia, 12, 2010.
24. J. Yuan, Z. Zha, Z. Zhao, X. Zhou, and T. Chua. Utilizing related samples to learn complex queries in interactive concept-based video search. In Proceedings of the ACM International Conference on Image and Video Retrieval, pages 66-73, 2010.
25. Z.-J. Zha, X.-S. Hua, T. Mei, J. Wang, G.-J. Qi, and Z. Wang. Joint multi-label multi-instance learning for image classification. In Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, pages 1-8, 2008.
26. Z.-J. Zha, M. Wang, Y.-T. Zheng, Y. Yang, R. Hong, and T.-S. Chua. Interactive video indexing with statistical active learning. IEEE Transaction on Multimedia, 14(1):17-27, 2012.
27. Z.-J. Zha, L. Yang, T. Mei, M. Wang, and Z. Wang. Visual query suggestion. In Proc. of the ACM International Conference on Multimedia, pages 15-24, 2009.
28. Z.-J. Zha, L. Yang, T. Mei, M. Wang, Z. Wang, T.-S. Chua, and X.-S. Hua. Visual query suggestion: Towards capturing user intent in internet image search. ACM Transactions on Multimedia Computing, Communications and Applications, 6(3):1-19, 2010.