ARCHIVES

[1]. Tsampoulatidis, I., Gkalelis, N., Dimou, A., Mezaris, V., & Kompatsiaris, I. (2011). High-level event detection system based on
discriminant visual concepts. Proceedings of the 1st ACM International Conference on Multimedia Retrieval, 1-2.
[2]. 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. Proceedings of the Fourth ACM Conference on Recommender Systems, September
26-30.
[3]. Zhou, R., Khemmarat, S., Gao, L., & Wang, H. (2011). Boosting Video Popularity through Recommendation Systems. DBSocial '11:
Databases and Social Networks, 13- 18.
[4]. Baluja, S., Seth, R., Sivakumar, D., Jing, Y., Yagnik, J., Kumar, S., Ravichandran, D., & Aly, M. (2008). Video suggestion and discovery
for YouTube: Taking random walks through the view graph. Proceeding of the 17th International Conference on World Wide Web, April
21-25.
[5]. Qin, S., Menezes, R., & Silaghi, M. (2010). A Recommender System for YouTube Based on its Network of Reviewers. Social Computing
(SocialCom), 2010 IEEE Second International Conference on, 323-328.
[6]. Mei, T., Yang, B., Hua, X-S., & Li, S. (2011). Contextual Video Recommendation by Multimodal Relevance and User Feedback. ACM
Transactions on Information Systems, 29(2).
[7]. Renjie, Z., Khemmarat, S., & Gao, L. (2010). The impact of YouTube recommendation system on video views. Proceedings of the 10th
Annual Conference on Internet Measurement, November 01-30.
[8]. Jayavardhana Gubbi, Rajkumar Buyya, Slaven Marusic, and Marimuthu Palaniswami. Internet of things (iot): A vision, architectural
elements, and future directions. Future generation computer systems, 29(7):1645-1660, 2013.
[9]. Aristomenis S Lampropoulos and George A Tsihrintzis. Machine Learning Paradigms: Applications in Recommender Systems, volume
92. Springer, 2015.