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Edge-based Local Push for Personalized PageRank

Summary: Introduces EdgePush, an edge-granular LocalPush variant for SSPPR on weighted graphs that avoids propagating probability along negligible-weight edges. Per-edge termination thresholds provide up to O(n) theoretical savings on unbalanced graphs and substantial empirical speedups. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
12833
Venue
VLDB
Year
2022
Pagerank
6.3495351e-05
Overall Rank
5,139 | 64.75%
DOI
10.14778/3523210.3523216

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{wang_vldb22,
        title = {{Edge-based Local Push for Personalized PageRank}},
        author = {Wang, Hanzhi and Wei, Zhewei and Gan, Junhao and Yuan, Ye and Du, Xiaoyong and Wen, Ji-Rong},
        journal = {PVLDB},
        series = {{VLDB} '22},
        volume = {15},
        number = {7},
        pages = {1376--1389},
        doi = {10.14778/3523210.3523216},
        url = {https://doi.org/10.14778/3523210.3523216},
        year = {2022}
}

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