Research paper on user trajectory prediction withdrawn by author

A research paper titled "User Trajectory Prediction Unifying Global and Local Temporal Information" was submitted to arXiv, proposing a novel model that combines multilayer perceptron (MLP), multi-scale convolutional neural network (MSCNN), and cross-attention (CA) to improve trajectory forecasting. The model aims to capture both global and local temporal patterns in user mobility data, addressing challenges related to different time scales of user behavior. Experimental results indicated a reduction in mean squared error (MSE) and mean absolute error (MAE) compared to the ModernTCN model, while maintaining similar inference times. However, the paper has since been withdrawn by its author, Wei Hao. AI

IMPACT This research, though withdrawn, explored novel methods for trajectory prediction, potentially influencing future work in areas requiring user mobility analysis.

RANK_REASON The item describes a research paper submitted to arXiv, detailing a novel model and its experimental results. [lever_c_demoted from research: ic=1 ai=1.0]

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