Exploring the Risky Travel Area and Behavior of Car-hailing Service

doi:10.1145/3465059

	Exploring the Risky Travel Area and Behavior of Car-hailing Service
	Niu, Hongting 1; Zhu, Hengshu 2; Sun, Ying 3; Lu, Xinjiang 4; Sun, Jing 5; Zhao, Zhiyuan 1; Xiong, Hui 6; Lang, Bo 1
	2022-02-01
发表期刊	ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY
ISSN	2157-6904
卷号	13 期号:1 页码:22
摘要	Recent years have witnessed the rapid development of car-hailing services, which provide a convenient approach for connecting passengers and local drivers using their personal vehicles. At the same time, the concern on passenger safety has gradually emerged and attracted more and more attention. While car-hailing service providers have made considerable efforts on developing real-time trajectory tracking systems and alarm mechanisms, most of them only focus on providing rescue-supporting information rather than preventing potential crimes. Recently, the newly available large-scale car-hailing order data have provided an unparalleled chance for researchers to explore the risky travel area and behavior of car-hailing services, which can be used for building an intelligent crime early warning system. To this end, in this article, we propose a Risky Area and Risky Behavior Evaluation System (RARBEs) based on the real-world car-hailing order data. In RARBEs, we first mine massive multi-source urban data and train an effective area risk prediction model, which estimates area risk at the urban block level. Then, we propose a transverse and longitudinal double detection method, which estimates behavior risk based on two aspects, including fraud trajectory recognition and fraud patterns mining. In particular, we creatively propose a bipartite graph-based algorithm to model the implicit relationship between areas and behaviors, which collaboratively adjusts area risk and behavior risk estimation based on random walk regularization. Finally, extensive experiments on multi-source real-world urban data clearly validate the effectiveness and efficiency of our system.
关键词	Risk analysis fraud detection bipartite graph optimization order sequence syndrome anomaly detection
DOI	10.1145/3465059
收录类别	SCI
语种	英语
资助项目	State Key Laboratory of Software Development Environment[SKLSDE2021ZX-19] ; State Key Laboratory of Software Development Environment[SKLSDE-2020ZX-02]
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Information Systems
WOS记录号	WOS:000759299400007
出版者	ASSOC COMPUTING MACHINERY
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/18957
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Niu, Hongting
作者单位	1.Beihang Univ, State Key Lab Software Dev Environm, Beijing 100190, Peoples R China 2.Baidu Inc, Baidu Talent Intelligence Ctr, Beijing 100085, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 4.Baidu Inc, Business Intelligency Lab, Beijing 100085, Peoples R China 5.East China Univ Polit Sci & Law, Shanghai, Peoples R China 6.Hong Kong Univ Sci & Technol, Artificial Intelligence Thrust, Guangzhou 511453, Peoples R China
推荐引用方式 GB/T 7714	Niu, Hongting,Zhu, Hengshu,Sun, Ying,et al. Exploring the Risky Travel Area and Behavior of Car-hailing Service[J]. ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY,2022,13(1):22.
APA	Niu, Hongting.,Zhu, Hengshu.,Sun, Ying.,Lu, Xinjiang.,Sun, Jing.,...&Lang, Bo.(2022).Exploring the Risky Travel Area and Behavior of Car-hailing Service.ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY,13(1),22.
MLA	Niu, Hongting,et al."Exploring the Risky Travel Area and Behavior of Car-hailing Service".ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY 13.1(2022):22.