Approximating Probabilistic Group Steiner Trees in Graphs
Summary: Formulates probabilistic group Steiner trees for uncertain vertex properties, requiring threshold joint coverage of every PoI at minimum edge cost. Provides three approximation algorithms trading tight |Γ|/ξ guarantees against exponential versus polynomial time, outperforming prior work empirically. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Shuang Yang (Renmin University of China)
- 2. Yahui Sun (Renmin University of China)
- 3. Jiesong Liu (Renmin University of China)
- 4. Xiaokui Xiao (National University of Singapore)
- 5. Rong-Hua Li (Beijing Institute of Technology)
- 6. Zhewei Wei (Renmin University of China)
BibTeX Citation
@article{yang_vldb23,
title = {{Approximating Probabilistic Group Steiner Trees in Graphs}},
author = {Yang, Shuang and Sun, Yahui and Liu, Jiesong and Xiao, Xiaokui and Li, Rong-Hua and Wei, Zhewei},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {2},
pages = {343--355},
doi = {10.14778/3565816.3565834},
url = {https://doi.org/10.14778/3565816.3565834},
year = {2023}
}
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,370 | Fast Optimal Group Steiner Tree Search using GPUs | 2026 | SIGMOD | 5.093636e-05 |
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