Online Prediction Algorithm of the News' Popularity for Wireless Cellular Pushing

被引：0
|
作者：
Chen, Huangqing [1 ]
Zhong, Xiaofeng [1 ]
Sun, Jian [1 ]
Wang, Jing [1 ]
机构：
[1] Tsinghua Univ, Dept Elect Engn, Tsinghua Natl Lab Informat Sci & Technol, Beijing 100084, Peoples R China
来源：
2015 IEEE/CIC INTERNATIONAL CONFERENCE ON COMMUNICATIONS IN CHINA (ICCC) | 2015年
关键词：
online news; popularity prediction; clicks; wireless cellular network; rank;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
There is an obviously converging property of online news browsed by mobile users, and a small number of popular contents play an important role in data traffic of wireless cellular network. Therefore, if we are able to estimate the grade of news' popularity from early observation of users' clicks, the transmitting resources would be saved significantly by broadcasting the top-N popular news to mobile devices of potential users. In this paper, we present an improved linear prediction scheme on a logarithmic scale, which uses an optimal observation threshold to make better performance of prediction. And the proposed prediction scheme is compared with classic rank algorithms using machine learning techniques. Based on data set collected from Chinese commercial cellular network, the simulation results indicate that this scheme provides a much better prediction accuracy as evaluated by Normal Discounted Cumulative Gain (NDCG) metric.
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页数：5
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