Efficient Computation of Feedback Arc Set at Web-Scale
Summary: Algorithm-engineering study of minimum feedback arc set approximations, showing greedy and randomized methods achieve strong size–runtime tradeoffs on web graphs with billions of vertices. Extends and evaluates them under probabilistic edge realization. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Michael Simpson (University of Victoria)
- 2. Venkatesh Srinivasan (University of Victoria)
- 3. Alex Thomo (University of Victoria)
BibTeX Citation
@article{simpson_vldb17,
title = {{Efficient Computation of Feedback Arc Set at Web-Scale}},
author = {Simpson, Michael and Srinivasan, Venkatesh and Thomo, Alex},
journal = {PVLDB},
series = {{VLDB} '17},
volume = {10},
number = {3},
pages = {133--144},
doi = {10.14778/3021924.3021927},
url = {https://doi.org/10.14778/3021924.3021927},
year = {2017}
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,977 | Injecting Uncertainty in Graphs for Identity Obfuscation | 2012 | VLDB | 7.9035901e-05 |
| 6,970 | Linearized and Single-Pass Belief Propagation | 2015 | VLDB | 5.7303405e-05 |
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