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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)

Paper ID
13364
Venue
VLDB
Year
2023
Pagerank
5.093636e-05
Overall Rank
11,463 | 21.36%
DOI
10.14778/3565816.3565834

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Authors

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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