A review of user identity matching methods based on trajectory data
With the continuous improvement of urban traffic fine-grained governance requirements,traditional traffic surveys struggle to adapt to residents'rapidly changing travel patterns.The emergence and development of new technologies and business models have enabled traveler trajectories to be recorded in a large-scale,high-frequency and low-cost manner.Fusing multiple sources of anonymized data to construct a complete multi-modal travel chain of travelers without violating users'privacy,which can effectively complement existing traffic survey methods.This paper explores various user identity-matching methods based on trajectory similarity and data characteristics,and discusses the directions for future research.
human mobilitytrajectory dataurban computinguser identity linkage
NETL
NSTL
万方数据
