Multimedia Recommendation
Publication Type
Presentation
Publication Date
10-2012
Abstract
Due to the rapid growth of online multimedia information, the problem of information overload has become more and more serious in recent decades. To address this problem, various multimedia recommendation technologies have been developed by different research communities (e.g., multimedia systems, information retrieval, and machine learning). Meanwhile, many commercial web systems (e.g., Flick, Youtube, and Last.fm) have successfully applied recommendation techniques to provide users personalized multimedia content and services in a convenient and flexible way. Half-day tutorial.
Discipline
Databases and Information Systems | Numerical Analysis and Scientific Computing
Publication
20th ACM International Conference on Multimedia (ACM MM 2012)
City or Country
Nara, Japan
Citation
SHEN, Jialie; WANG, Meng; YAN, Shuicheng; and CUI, Peng.
Multimedia Recommendation. (2012). 20th ACM International Conference on Multimedia (ACM MM 2012).
Available at: https://ink.library.smu.edu.sg/sis_research/1553