Statistical Properties and Temporal Properties of Calling Behavior
文献类型：会议论文
| 作者 | Gui J(桂珺)1,2,3,4 ; Zheng ZY(郑泽宇)3,4; Zhao XF(赵雪峰)3,4; Qin ZB(秦兆伯 )2
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| 出版日期 | 2019 |
| 会议日期 | December 6-9, 2019 |
| 会议地点 | Chengdu, China |
| 关键词 | call frequency call duration power law distribution log normal distribution circadian cycle |
| 页码 | 1940-1944 |
| 英文摘要 | Modern information technology makes it possible to understand, model and predict human activities by analyzing electronic traces of human behavior. In this work, we analyze more than 30 million Call Data Records (CDRs) to investigate statistical properties and temporal properties of calling behavior. We find that ranked call frequency of each number can be described by a two-stage power law function. The distribution of call duration is much different and can be described by a bimodal log-normal function. Further, we confirm that both call frequency and call duration are related with circadian cycles. During daylight, call duration is strongly correlated with call frequency. However, during evening and midnight, the pattern of call duration is much different with the pattern of call frequency. Our findings have significant impact on modeling human calling activity and optimizing telecommunication services. |
| 产权排序 | 1 |
| 会议录 | 2019 IEEE 5th International Conference on Computer and Communications, ICCC 2019
 |
| 会议录出版者 | IEEE |
| 会议录出版地 | NEW YORK |
| 语种 | 英语 |
| ISBN号 | 978-1-7281-4743-7 |
| 源URL | [http://ir.sia.cn/handle/173321/26757]  |
| 专题 | 沈阳自动化研究所_数字工厂研究室 |
| 通讯作者 | Gui J(桂珺) |
| 作者单位 | 1.University of Chinese Academy of Sciences, Beijing 100049, China 2.Shenyang University of Technology, School of Information Science and Engineering, Shenyang 110870, China 3.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 4.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China |
| 推荐引用方式 GB/T 7714 | Gui J,Zheng ZY,Zhao XF,et al. Statistical Properties and Temporal Properties of Calling Behavior[C]. 见:. Chengdu, China. December 6-9, 2019. |
入库方式： OAI收割
来源：沈阳自动化研究所
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