Travel Cost Inference from Sparse, Spatio-Temporally Correlated Time Series Using Markov Models
Summary: Introduces spatio-temporal hidden Markov models for inferring missing and near-future road-segment travel costs from sparse, correlated GPS time series. Learns heterogeneous model parameters despite sparsity, enabling efficient traffic prediction and eco-routing. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Bin Yang (Aarhus University)
- 2. Chenjuan Guo (Aarhus University)
- 3. Christian S. Jensen (Aarhus University)
BibTeX Citation
@article{yang_vldb13,
title = {{Travel Cost Inference from Sparse, Spatio-Temporally Correlated Time Series Using Markov Models}},
author = {Yang, Bin and Guo, Chenjuan and Jensen, Christian S.},
journal = {PVLDB},
series = {{VLDB} '13},
volume = {6},
number = {9},
pages = {769--780},
doi = {10.14778/2501551.2501557},
url = {https://doi.org/10.14778/2501551.2501557},
year = {2013}
}Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,694 | Anytime Stochastic Routing with Hybrid Learning | 2020 | VLDB | 7.1937882e-05 |
| 5,129 | AutoCTS: Automated Correlated Time Series Forecasting | 2022 | VLDB | 6.3548172e-05 |
| 9,230 | Path Cost Distribution Estimation Using Trajectory Data | 2017 | VLDB | 5.3017894e-05 |
| 11,254 | Efficient Stochastic Routing in Path-Centric Uncertain Road Networks | 2024 | VLDB | 5.093636e-05 |
| 11,442 | Effective and Efficient Route Planning Using Historical Trajectories on Road Networks | 2023 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 1 of 1 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,399 | Finding Semantics in Time Series | 2011 | SIGMOD | 7.4466526e-05 |
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