Adversarial Mobility Learning for Human Trajectory Classification

Adversarial Mobility Learning for Human Trajectory Classification

Understanding human mobility is one of the important but challenging tasks in Location-based Social Networks (LBSN). Recently, a user mobility mining task called Trajectory User Linking (TUL) has become an essential and popular topic, aiming at identifying user identities through exploiting their mo...

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Bibliographic Details
Main Authors: Qiang Gao, Fengli Zhang, Fuming Yao, Ailing Li, Lin Mei, Fan Zhou
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Trajectory user linking
adversarial model
autoencoder
attention mechanism
human mobility
Online Access:https://ieeexplore.ieee.org/document/8967063/

Internet

https://ieeexplore.ieee.org/document/8967063/

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