MDTP: A Multi-source Deep Traffic Prediction Framework over Spatio-Temporal Trajectory Data
Summary: MDTP: a two-phase framework for multi-source spatio-temporal trajectory data using a GCN-LSTM to model spatial and temporal dynamics. Sum and Concat bridge sources to deliver multi-source gains and high efficiency, scalable to tens of millions of trajectories, with the MDTP+ interactive system. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Ziquan Fang
- 2. Lu Pan
- 3. Lu Chen
- 4. Yuntao Du
- 5. Yunjun Gao
Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,234 | BigST: Linear Complexity Spatio-Temporal Graph Neural Network for Traffic Forecasting on Large-Scale Road Networks | 2024 | VLDB | 7.3355287e-05 |
| 4,206 | Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting | 2022 | VLDB | 6.3595566e-05 |
| 8,744 | A Multi-Scale Decomposition MLP-Mixer for Time Series Analysis | 2024 | VLDB | 4.456315e-05 |
| 10,593 | Scalable Pre-Training of Compact Urban Spatio-Temporal Predictive Models on Large-Scale Multi-Domain Data | 2025 | VLDB | 4.1945683e-05 |
| 10,867 | T-Assess: An Efficient Data Quality Assessment System Tailored for Trajectory Data | 2025 | VLDB | 4.1945683e-05 |
| 11,188 | ST4ML: Machine Learning Oriented Spatio-Temporal Data Processing at Scale | 2023 | SIGMOD | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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