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An In-Depth Comparison of s-t Reliability Algorithms over Uncertain Graphs

Summary: Unified re-implementation and benchmark of six s-t reliability estimators on uncertain graphs, using consistent datasets, metrics, and workloads. Surprising results: many later algorithms are slower, less accurate, and more memory-hungry than early methods; recommendations. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12199
Venue
VLDB
Year
2019
Pagerank
6.0496722e-05
Overall Rank
5,890 | 59.60%
DOI
10.14778/3324301.3324304

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{ke_vldb19,
        title = {{An In-Depth Comparison of s-t Reliability Algorithms over Uncertain Graphs}},
        author = {Ke, Xiangyu and Khan, Arijit and Quan, Leroy Lim Hong},
        journal = {PVLDB},
        series = {{VLDB} '19},
        volume = {12},
        number = {8},
        pages = {864--876},
        doi = {10.14778/3324301.3324304},
        url = {https://doi.org/10.14778/3324301.3324304},
        year = {2019}
}

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