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Semantics Analytics of Origin-Destination Flows from Crowd Sensed Big Data

Ning Cao1,2, Shengfang Li1, Keyong Shen1, Sheng Bin3, Gengxin Sun3,*, Dongjie Zhu4, Xiuli Han5, Guangsheng Cao5, Abraham Campbell6
College of Computer Information and Engineering, Nanchang Institute of Technology, Nanchang, China.
College of Information Engineering, Sanming University, Sanming, China.
School of Data Science and Software Engineering, Qingdao University, Qingdao, China.
School of Computer Science and Technology, Harbin Institute of Technology, Weihai, China.
Public Teaching Department, Qingdao Technical College, Qingdao, China.
School of Computer Science, University College Dublin, Dublin, Ireland.
* Corresponding Author: Gengxin Sun. Email: .

Computers, Materials & Continua 2019, 61(1), 227-241. https://doi.org/10.32604/cmc.2019.06125

Abstract

Monitoring, understanding and predicting Origin-destination (OD) flows in a city is an important problem for city planning and human activity. Taxi-GPS traces, acted as one kind of typical crowd sensed data, it can be used to mine the semantics of OD flows. In this paper, we firstly construct and analyze a complex network of OD flows based on large-scale GPS taxi traces of a city in China. The spatiotemporal analysis for the OD flows complex network showed that there were distinctive patterns in OD flows. Then based on a novel complex network model, a semantics mining method of OD flows is proposed through compounding Points of Interests (POI) network and public transport network to the OD flows network. The propose method would offer a novel way to predict the location characteristic and future traffic conditions accurately.

Keywords

Origin-destination (OD) flows, semantics analytics, complex network, big data analysis

Cite This Article

N. Cao, S. Li, K. Shen, S. Bin, G. Sun et al., "Semantics analytics of origin-destination flows from crowd sensed big data," Computers, Materials & Continua, vol. 61, no.1, pp. 227–241, 2019.

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This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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