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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
hebfd4b9610247c72
Venue
SIGMOD
Year
2021
Pagerank
8.8962182e-05
Overall Rank
2,183 | 85.33%
DOI
10.1145/3448016.3457298
Incoming Non-self Citations Over Time
BibTeX Citation
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@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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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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Year
Venue
Pagerank
556
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2011
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0.00010728945
1,604
Fast and Unified Local Search for Random Walk Based K-Nearest-Neighbor Query in Large Graphs
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