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Discovering Fine-Grained Spatial Pattern From Taxi Trips: Where Point Process Meets Matrix Decomposition and Factorization

文献类型：期刊论文

作者Pang, Junbiao1; Huang, Jing1; Yang, Xue2; Wang, Zuyun3; Yu, Haitao2; Huang, Qingming4,5; Yin, Baocai6,7
刊名IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
出版日期2018-10-01
卷号19期号:10页码:3208-3219
关键词Spatio-temporal pattern fine-grained pattern low-rank regularity matrix factorization taxis trip point process
ISSN号1524-9050
DOI10.1109/TITS.2017.2771262
英文摘要As increasing volumes of urban data are being available, new opportunities arise for data-driven analysis that can lead to improvements in the lives of citizens through evidence-based policies. In particular, taxi trip is an important urban sensor that provides unprecedented insights into many aspects of a city, from economic activity, human mobility to land development. However, analyzing these data presents many challenges, e.g., sparse data for fine-grained patterns, and the regularity submerged by seemingly random data. Inspired by above challenges, we focus on Pick-Up (PU)/Drop-Off (DO) points from taxi trips, and propose a fine-grained approach to unveil a set of low spatio-temporal patterns from the regularity-discovered intensity. The proposed method is conceptually simple yet efficient, by leveraging point process to handle sparsity of points, and by decomposing point intensities into the low-rank regularity and the factorized basis patterns, our approach enables domain experts to discover patterns that are previously unattainable for them, from a case study motivated by traffic engineers.
资助项目Natural Science Foundation of China[61672069] ; Natural Science Foundation of China[61472387] ; Natural Science Foundation of China[61332016] ; Natural Science Foundation of China[61620106009] ; Beijing Post-Doctoral Research Foundation ; China Postdoctoral Science Foundation ; Beijing Municipal Commission of Education[KM201610005034] ; Funding Project for Academic Human Resources Development in Institutions of Higher Learning through the Jurisdiction of Beijing Municipality ; Beijing Municipal Commission of Transport Science and Technology Project
WOS研究方向Engineering ; Transportation
语种英语
WOS记录号WOS:000446651100011
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
源URL[http://119.78.100.204/handle/2XEOYT63/4852]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Pang, Junbiao; Yu, Haitao
作者单位1.Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
2.Beijing Transportat Informat Ctr, Beijing 100161, Peoples R China
3.Beijing Municipal Transportat Law Enforcement Cor, Beijing 100044, Peoples R China
4.Univ Chinese Acad Sci, Chinese Acad Sci, Beijing 100049, Peoples R China
5.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China
6.Dalian Univ Technol, Adv Invocat Ctr Future Internet Technol, Dalian 116024, Peoples R China
7.Beijing Univ Technol, Beijing 100124, Peoples R China
推荐引用方式
GB/T 7714		 Pang, Junbiao,Huang, Jing,Yang, Xue,et al. Discovering Fine-Grained Spatial Pattern From Taxi Trips: Where Point Process Meets Matrix Decomposition and Factorization[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2018,19(10):3208-3219.
APA Pang, Junbiao.,Huang, Jing.,Yang, Xue.,Wang, Zuyun.,Yu, Haitao.,...&Yin, Baocai.(2018).Discovering Fine-Grained Spatial Pattern From Taxi Trips: Where Point Process Meets Matrix Decomposition and Factorization.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,19(10),3208-3219.
MLA Pang, Junbiao,et al."Discovering Fine-Grained Spatial Pattern From Taxi Trips: Where Point Process Meets Matrix Decomposition and Factorization".IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 19.10(2018):3208-3219.

入库方式： OAI收割

来源：计算技术研究所

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