TY - JOUR
T1 - A cloud-based intelligent TV program recommendation system
AU - Chang, Jui Hung
AU - Lai, Chin Feng
AU - Wang, Ming Shi
AU - Wu, Tin Yu
N1 - Funding Information:
The authors would like to thank the National Science Council of the Republic of China, Taiwan for supporting this research under Contract NSC 101-2628-E-197-001- MY3, 101-2221-E-197-008-MY3 and 101-2219-E-197-004.
PY - 2013/10
Y1 - 2013/10
N2 - In recent years, cloud computing technology has matured significantly, as has the development of digital TV services. This, therefore, has led to an increased demand for improved quality TV services. In: this paper, cloud computing technology is used to build a program recommendation system for digital TV programs, and the Hadoop Fair Scheduler is utilized to improve processing performance. Historical data of watched TV programs are collected through an electronic program guide, and then processed using K-means clustering, term frequency/inverse document frequency and k-nearest neighbor algorithms, to obtain clusters of audience groups and to find popular TV programs for each cluster. The proposed system can process massive amounts of user data in real-time, and can easily be scaled up.
AB - In recent years, cloud computing technology has matured significantly, as has the development of digital TV services. This, therefore, has led to an increased demand for improved quality TV services. In: this paper, cloud computing technology is used to build a program recommendation system for digital TV programs, and the Hadoop Fair Scheduler is utilized to improve processing performance. Historical data of watched TV programs are collected through an electronic program guide, and then processed using K-means clustering, term frequency/inverse document frequency and k-nearest neighbor algorithms, to obtain clusters of audience groups and to find popular TV programs for each cluster. The proposed system can process massive amounts of user data in real-time, and can easily be scaled up.
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U2 - 10.1016/j.compeleceng.2013.04.025
DO - 10.1016/j.compeleceng.2013.04.025
M3 - Article
AN - SCOPUS:84885574873
SN - 0045-7906
VL - 39
SP - 2379
EP - 2399
JO - Computers and Electrical Engineering
JF - Computers and Electrical Engineering
IS - 7
ER -