MDTP: A Multi-source Deep Traffic Prediction Framework over Spatio-Temporal Trajectory Data

Summary: MDTP jointly models multiple trajectory sources, combining enhanced GCN–LSTM spatio-temporal learning with Sum/Concat feature bridging. It improves over single-source and prior predictors while scaling to tens of millions of trajectories with second-level latency. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID: 12507
Venue: VLDB
Year: 2021
Pagerank: 7.0361711e-05
Overall Rank: 3,899 | 73.26%
DOI: 10.14778/3457390.3457394

Incoming Non-self Citations Over Time

Authors

1. Ziquan Fang (Zhejiang University)
2. Lu Pan (Zhejiang University)
3. Lu Chen (Zhejiang University)
4. Yuntao Du (Zhejiang University)
5. Yunjun Gao (Alibaba; Zhejiang University)

BibTeX Citation

@article{fang_vldb21,
        title = {{MDTP: A Multi-source Deep Traffic Prediction Framework over Spatio-Temporal Trajectory Data}},
        author = {Fang, Ziquan and Pan, Lu and Chen, Lu and Du, Yuntao and Gao, Yunjun},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {8},
        pages = {1289--1297},
        doi = {10.14778/3457390.3457394},
        url = {https://doi.org/10.14778/3457390.3457394},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 6 of 6 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
4,038	BigST: Linear Complexity Spatio-Temporal Graph Neural Network for Traffic Forecasting on Large-Scale Road Networks	2024	VLDB	6.9431109e-05
4,589	Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting	2022	VLDB	6.6162897e-05
8,915	A Multi-Scale Decomposition MLP-Mixer for Time Series Analysis	2024	VLDB	5.3483178e-05
10,854	Scalable Pre-Training of Compact Urban Spatio-Temporal Predictive Models on Large-Scale Multi-Domain Data	2025	VLDB	5.093636e-05
11,090	T-Assess: An Efficient Data Quality Assessment System Tailored for Trajectory Data	2025	VLDB	5.093636e-05
11,392	ST4ML: Machine Learning Oriented Spatio-Temporal Data Processing at Scale	2023	SIGMOD	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 0 of 0 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank

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