Performance comparison of destination prediction with baselines on two datasets.

Performance comparison of destination prediction with baselines on two datasets.

<p>Performance comparison of destination prediction with baselines on two datasets.</p>

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Bibliographic Details
Main Author:	Dan Luo (192943) (author)
Other Authors:	Fang Zhao (11980) (author), Hao Zhou (136535) (author), Chenxing Wang (1744246) (author), Hao Xiong (86981) (author)
Published:	2025
Subjects:	Sociology Biological Sciences not elsewhere classified Information Systems not elsewhere classified urban traffic management individual &# 8217 grained spatial dependencies future travel destinations entropy loss function constrained modeling capability trajectory subsequence alignment sparse trajectory scenarios enhancing prediction accuracy balance global patterns task learning framework task learning approach intelligent travel recommendations historical trajectory data task learning trajectory data prediction tasks personalized recommendations intelligent navigation diverse patterns missing data data sparsity sparsity handling public datasets paper proposes outperforming state low quality local volatility local features insufficient integration inadequate exploration improving robustness experimental results convolutional operations art baselines accurately forecast 64 %.
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Summary:	<p>Performance comparison of destination prediction with baselines on two datasets.</p>

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