Trajectory Simplification: On Minimizing the Direction-based Error
Summary: Defines Min-Error for direction-preserving trajectory simplification (DPTS) under a fixed output size, removing reliance on user-specified tolerances by directly minimizing error. Proposes two exact algorithms and a 2-approximation algorithm; experiments on real datasets validate efficiency and accuracy. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Cheng Long (Hong Kong University of Science and Technology)
- 2. Raymond Chi-Wing Wong (Hong Kong University of Science and Technology)
- 3. H. V. Jagadish (University of Michigan)
BibTeX Citation
@article{long_vldb15,
title = {{Trajectory Simplification: On Minimizing the Direction-based Error}},
author = {Long, Cheng and Wong, Raymond Chi-Wing and Jagadish, H. V.},
journal = {PVLDB},
series = {{VLDB} '15},
volume = {8},
number = {1},
doi = {10.14778/2735461.2735466},
url = {https://doi.org/10.14778/2735461.2735466},
year = {2015}
}
Incoming Citations (Sorted by Pagerank)
Showing 11 of 11 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,389 | Finding Time Period-Based Most Frequent Path in Big Trajectory Data | 2013 | SIGMOD | 0.00010817927 |
| 2,914 | Direction-Preserving Trajectory Simplification | 2013 | VLDB | 7.8619624e-05 |
| 4,763 | EBM - An Entropy-Based Model to Infer Social Strength from Spatiotemporal Data | 2013 | SIGMOD | 6.4294394e-05 |
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