Efficient and Flexible Pipeline for Spatio-Temporal Trajectory Graph Modeling and Representation Learning

Efflex, a comprehensive pipeline for transformative graph modeling and representation learning of large-volume spatio-temporal trajectories, leverages a multi-scale k-nearest neighbors (KNN) algorithm with feature fusion for efficient and accurate graph construction, and a custom-built lightweight Graph Convolutional Network (GCN) for fast and competitive embedding extraction.