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Detecting unmetered taxi rides from trajectory data
Zhou, Xibo1; Ding, Ye2; Peng, Fengchao1; Luo, Qiong1; Ni, Lionel M.3
2018-01-12
Conference Name5th IEEE International Conference on Big Data, Big Data 2017
Source PublicationProceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
Volume2018-January
Pages530-535
Conference Date1211, 2017 - 1214, 2017
Conference PlaceBoston, MA, United states
Author of SourceInstitute of Electrical and Electronics Engineers Inc.
AbstractTaxi fraud has become a serious problem in many large cities, where passengers are overcharged by taxi drivers in various ways. Researchers have developed a number of methods to detect taxi frauds with the assumption that fraudulent trips, among normal trips, are recorded by taximeters. In this paper, different from the previous work, we identify a new type of taxi fraud called unmetered taxi rides, where taxi drivers carry passengers without activating the taximeters. Since these fraudulent rides are not recorded by taximeters, previous detection approaches cannot directly apply to them. Hence, we propose a novel fraud detection system specifically designed for unmetered taxi rides. Our system uses a learning model to detect unmetered trajectory segments that are similar to metered rides, and introduces a heuristic algorithm to construct maximum fraudulent trajectories from the trajectory dataset. We have conducted detailed experiments on real-world datasets, and the results show that the proposed system can detect unmetered taxi rides effectively and efficiently. © 2017 IEEE.
DOI10.1109/BigData.2017.8257968
Language英语
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Document TypeConference paper
CollectionUniversity of Macau
Affiliation1.Department of Science and Engineering, Hong Kong University of Science and Technology, Hong Kong;
2.Guangzhou HKUST Fok Ying Tung Research Institute, Hong Kong University of Science and Technology, Hong Kong;
3.University of Macau, China
Recommended Citation
GB/T 7714
Zhou, Xibo,Ding, Ye,Peng, Fengchao,et al. Detecting unmetered taxi rides from trajectory data[C]//Institute of Electrical and Electronics Engineers Inc.,2018:530-535.
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