Anchor points seeking of large urban crowd based on the mobile billing data

Authors:
Wenhao Huang;Zhengbin Dong;Nan Zhao;Hao Tian;Guojie Song;Guanhua Chen;Yun Jiang;Kunqing Xie
Affiliations:
Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, China;Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, China;Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, China;Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, China;Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, China;Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, China;Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, China;Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, China
Venue:
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications: Part I
Year:
2010

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Abstract

In everyday life, people spend most of their time in some routine places such as the living places(origin) and working places(destination). We define these locations as anchor points. The anchor point information is important to the city planning, transportation management and optimization. Traditional methods of anchor points seeking mainly based on the data obtained from the sample survey or link volumes. The defects of these methods such as low sample rate and high cost make it difficult for us to study on the large crowd in the city.In recent years, with the rapid development of wireless communication, mobile phones have becoming more and more popular. In this paper, we proposed a novel approach to obtain the anchor points of the large urban crowd based on the mobile billing data. In addition, we took advantage of the spatial and temporal patterns of people's behavior in the anchor points to improve the simple algorithm.