Human Network Usage Patterns Revealed by Telecom Data

被引：0
|
作者：
Kong, Yining [1 ]
Zang, Hui [2 ]
Ma, Xiaoli [1 ]
机构：
[1] Georgia Tech, Sch ECE, Atlanta, GA 30332 USA
[2] Futurewei Technol Inc, 2330 Cent Expressway, Santa Clara, CA USA
来源：
2016 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA) | 2016年
关键词：
xDRs; modeling; heavy-tailed distributions; LAW;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Call detail records (CDRs) collected at telecommunication networks have been well studied to reveal human behaviors such as voice service usage, contact regularities and mobility patterns. With the advances in big data technology, carriers can now collect, store and analyze more data, such as records of user mobile web activities, at scales much larger than CDRs. In this paper, we study 14 features extracted from both call and web records through statistical modeling. We also analyze the impact of locations on voice usage, and examine the correlations between the usage of voice and web services. The results can be used in user profiling, service usage prediction, and network dimensioning.
引用
收藏
页码：1621 / 1626
页数：6
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