Finding Group Steiner Trees in Graphs with both Vertex and Edge Weights
Summary: Extends group Steiner tree algorithms to graphs with both vertex and edge weights, addressing a gap in prior work. Introduces scalable |Γ|-1 and tunable |Γ|-h+1 approximation algorithms, empirically outperforming existing methods. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Yahui Sun (National University of Singapore)
- 2. Xiaokui Xiao (National University of Singapore)
- 3. Bin Cui (Peking University)
- 4. Saman Halgamuge (University of Melbourne)
- 5. Theodoros Lappas (Stevens Institute of Technology)
- 6. Jun Luo (Nanyang Technological University)
BibTeX Citation
@article{sun_vldb21,
title = {{Finding Group Steiner Trees in Graphs with both Vertex and Edge Weights}},
author = {Sun, Yahui and Xiao, Xiaokui and Cui, Bin and Halgamuge, Saman and Lappas, Theodoros and Luo, Jun},
journal = {PVLDB},
series = {{VLDB} '21},
volume = {14},
number = {7},
pages = {1137--1149},
doi = {10.14778/3450980.3450982},
url = {https://doi.org/10.14778/3450980.3450982},
year = {2021}
}Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,370 | Fast Optimal Group Steiner Tree Search using GPUs | 2026 | SIGMOD | 5.093636e-05 |
| 11,463 | Approximating Probabilistic Group Steiner Trees in Graphs | 2023 | VLDB | 5.093636e-05 |
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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 |
|---|---|---|---|---|
| 1,878 | EASE: An Effective 3-in-1 Keyword Search Method for Unstructured, Semi-structured and Structured Data | 2008 | SIGMOD | 9.5651166e-05 |
| 6,469 | Efficient and Progressive Group Steiner Tree Search | 2016 | SIGMOD | 5.8710857e-05 |
| 11,826 | Hunting Multiple Bumps in Graphs | 2020 | VLDB | 5.093636e-05 |
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