Temporal patterns of the online video viewing behavior of smart TV viewers

被引:7
|
作者
Lian, Tao [1 ]
Chen, Zhumin [1 ]
Lin, Yujie [1 ]
Ma, Jun [1 ]
机构
[1] Shandong Univ, Sch Comp Sci & Technol, Jinan, Shandong, Peoples R China
关键词
RECOMMENDER SYSTEMS; SITUATIONS;
D O I
10.1002/asi.23992
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In recent years, millions of households have shifted from traditional TVs to smart TVs for viewing online videos on TV screens. In this article, we perform extensive analyses on a large-scale online video viewing log on smart TVs. Because time influences almost every aspect of our lives, our aim is to understand temporal patterns of the online video viewing behavior of smart TV viewers at the crowd level. First, we measure the amount of time per hour spent in watching online videos on smart TV by each household on each day. By applying clustering techniques, we identify eight daily patterns whose peak hours occur in different segments of the day. The differences among households can be characterized by three types of temporal habits. We also uncover five periodic weekly patterns. There seems to be a circadian rhythm at the crow level. Further analysis confirms that there exists a holiday effect in the online video viewing behavior on smart TVs. Finally, we investigate the popularity variations of different video categories over the day. The obtained insights shed light on how we can partition a day to improve the performance of time-aware video recommendations for smart TV viewers.
引用
收藏
页码:647 / 659
页数:13
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