One Index for All: Towards Efficient Personalized PageRank Computation for Every Damping Factor
Summary: Introduces StackIndex: a single stack-style meta-index built via loop-erased α-random walks with a large ᾱ that can be efficiently transformed to answer SSPPR for any damping factor α without rebuilding. Provably O(ω n) time/space construction, supports dynamic updates and yields large empirical speedups. (summarized by gpt-5-mini on Feb 11 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Junjie Zhou (Beijing Institute of Technology)
- 2. Meihao Liao (Beijing Institute of Technology)
- 3. Rong-Hua Li (Beijing Institute of Technology)
- 4. Longlong Lin (Southwest University)
- 5. Guoren Wang (Beijing Institute of Technology)
BibTeX Citation
@inproceedings{zhou_sigmod26,
title = {{One Index for All: Towards Efficient Personalized PageRank Computation for Every Damping Factor}},
author = {Zhou, Junjie and Liao, Meihao and Li, Rong-Hua and Lin, Longlong and Wang, Guoren},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3749176},
url = {https://dl.acm.org/doi/10.1145/3749176},
year = {2026}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,161 | Near-Optimality for Single-Source Personalized PageRank | 2026 | PODS | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 12 of 12 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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