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Unifying the Global and Local Approaches: An Efficient Power Iteration with Forward Push
Summary: PowerPush unifies Power Iteration and Forward Push for high-precision SSPPR, achieving O(m log(1/λ)) bound for FwdPush. SpeedPPR delivers fast approximate SSPPR on scale-free graphs with O(n log n log(1/ε)) time, outperforming BePI and FORA in time, accuracy, and index size.
(summarized by gpt-5-nano on Feb 09 2026)
Paper ID
6250
Venue
SIGMOD
Year
2021
Pagerank
9.0375634e-05
Overall Rank
2,173 | 85.10%
DOI
10.1145/3448016.3457298
Incoming Non-self Citations Over Time
BibTeX Citation
Copy BibTeX
@inproceedings{wu_sigmod21,
title = {{Unifying the Global and Local Approaches: An Efficient Power Iteration with Forward Push}},
author = {Wu, Hao and Gan, Junhao and Wei, Zhewei and Zhang, Rui},
series = {{SIGMOD} '21},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3448016.3457298},
url = {https://dl.acm.org/doi/10.1145/3448016.3457298},
year = {2021}
}
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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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Cited Paper
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Pagerank
556
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2011
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2014
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Fast and Exact Top-k Search for Random Walk with Restart
2012
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Fast and Unified Local Search for Random Walk Based K-Nearest-Neighbor Query in Large Graphs
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BEAR: Block Elimination Approach for Random Walk with Restart on Large Graphs
2015
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