中国邮电高校学报(英文) ›› 2016, Vol. 23 ›› Issue (1): 60-67.doi:

• Intelligence • 上一篇    下一篇

Affinity-based Human Mobility Pattern for Improved Region Function Discovering

徐雅静1,黎功福1,薛超1,罗安根1,宋一晢2   

  1. 1. 北京邮电大学
    2. Queen Mary University of London,British
  • 收稿日期:2015-04-27 修回日期:2015-09-21 出版日期:2016-02-26 发布日期:2016-02-28
  • 通讯作者: 黎功福 E-mail:buptlixin@163.com
  • 基金资助:

    基于非高斯概率模型的跨域视觉分析;基于图像配准与表示联合优化的自动人脸识别研究;基于激活力的复杂网络建模及其应用

Affinity-based Human Mobility Pattern for Improved Region Function Discovering

  • Received:2015-04-27 Revised:2015-09-21 Online:2016-02-26 Published:2016-02-28
  • Contact: Gong-Fu LI E-mail:buptlixin@163.com
  • Supported by:

    ;Activation force-based complex networks modeling and its applications

摘要:

The process of urbanization is formed by regular movements of human beings. It yields different functional zones in a city, such as residential zone and commercial zone. Consequently, there exists a close connection between the human mobility pattern and the city’s zones. However, it is not easy to collect large-scale society-wide data that can precisely capture the underlying relations between the individual’s movement and the regional functions. Hence, our knowledge for understanding the basic patterns of human mobility is still limited. In order to discover the functions of different regions in a city, we propose an affinity based method in this paper. The affinity is a recently introduced metric for measuring the correlation of two connecting node in a complex network. The proposed model groups different functional zones by measuring user’s arrival/departure distribution via relative entropy. In addition to this, we also identify the intensity of each functional zone by taking kernel density estimation method. In the end, some experiments are conducted to evaluate our method with a large-scale real-life dataset, which consists of 3 million cellphone users’ records from a period of one month. Our findings on the interaction between the mobility pattern and the regional functions can capture the city dynamics efficiently and provide a valuable reference for urban planners.

关键词:

Human mobility, functional regions, affinity measure

Abstract:

The process of urbanization is formed by regular movements of human beings. It yields different functional zones in a city, such as residential zone and commercial zone. Consequently, there exists a close connection between the human mobility pattern and the city’s zones. However, it is not easy to collect large-scale society-wide data that can precisely capture the underlying relations between the individual’s movement and the regional functions. Hence, our knowledge for understanding the basic patterns of human mobility is still limited. In order to discover the functions of different regions in a city, we propose an affinity based method in this paper. The affinity is a recently introduced metric for measuring the correlation of two connecting node in a complex network. The proposed model groups different functional zones by measuring user’s arrival/departure distribution via relative entropy. In addition to this, we also identify the intensity of each functional zone by taking kernel density estimation method. In the end, some experiments are conducted to evaluate our method with a large-scale real-life dataset, which consists of 3 million cellphone users’ records from a period of one month. Our findings on the interaction between the mobility pattern and the regional functions can capture the city dynamics efficiently and provide a valuable reference for urban planners.

Key words:

Human mobility, functional regions, affinity measure

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