Real-time bottleneck matching in spatial crowdsourcing

作     者：Long LI Lingling WANG Weifeng LV Long LI;Lingling WANG;Weifeng LV

作者机构：State Key Laboratory of Software Development Environment (SKLSDE Lab) and Beijing Advanced Innovation Center for Big Data and Brain Computing (BDBC)Beihang University School of Management and EconomicsBeijing Institute of Technology 

出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))

年 卷 期：2021年第64卷第8期

页      面：233-234页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0808[工学-电气工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by National Natural Science Foundation of China (Grant No. U11811463) 

主　　题：Real time bottleneck matching in spatial crowdsourcing 

摘      要：Dear editor,Spatial crowdsourcing(SC) services(e.g., Uber, DiDi, and Meituan) have become popular with smart-phone ***, the online matching problems in real-time spatial data are a key issue in SC [1–4]. Unlike the current one-sided online matching study in real-time spatial data [5], which focuses on minimizing the overall cost of the matching,