Trajectory-User Linking via Multi-Scale Graph Attention Network

Published: 01 Jan 2025, Last Modified: 08 Feb 2025Pattern Recognit. 2025EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Highlights•A multi-scale graph attention network for effective and efficient trajectory user linking•A graph construction method preserves the original trajectory context of arbitrary length.•A spatio-temporal network mines human mobility patterns in parallel and robustly.•Sufficient experiments prove its better performance and module validity.
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