Statistical Properties and Temporal Properties of Calling Behavior

CORC > 沈阳自动化研究所 > 中国科学院沈阳自动化研究所 > 数字工厂研究室

	Statistical Properties and Temporal Properties of Calling Behavior
	Gui J(桂珺)1,2,3,4; Zheng ZY(郑泽宇)1,3; Zhao XF(赵雪峰)1,3; Qin ZB(秦兆伯 )4
	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
内容类型	会议论文
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.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 2.University of Chinese Academy of Sciences, Beijing 100049, China 3.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China 4.Shenyang University of Technology, School of Information Science and Engineering, Shenyang 110870, 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.