The DOI matches its Crossref record; 22 of the 23 references it cites were found in a registry or an index.
Local Graph Partitioning using PageRank Vectors
Abstract
A local graph partitioning algorithm finds a cut near a specified starting vertex, with a running time that depends largely on the size of the small side of the cut, rather than the size of the input graph. In this paper, we present a local partitioning algorithm using a variation of PageRank with a specified starting distribution. We derive a mixing result for PageRank vectors similar to that for random walks, and show that the ordering of the vertices produced by a PageRank vector reveals a cut with small conductance. In particular, we show that for any set C with conductance Phi and volume k, a PageRank vector with a certain starting distribution can be used to produce a set with conductance (O(radic(Phi log k)). We present an improved algorithm for computing approximate PageRank vectors, which allows us to find such a set in time proportional to its size. In particular, we can find a cut with conductance at most oslash, whose small side has volume at least 2bin time O(2 log m/(2blog2m/oslash2) where m is the number of edges in the graph. By combining small sets found by this local partitioning algorithm, we obtain a cut with conductance oslash and approximately optimal balance in time O(m log4m/oslash)
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Metadata
- Authors
- Andersen, R., Chung, F., & Lang, K.
- Affiliations
- University of California San Diego (US)
- Yahoo (United States) (US)
- Venue
- 2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06)
- Publisher
- IEEE
- Published
- 2006
- Pages
- 475-486
- ISSN
- 0272-5428 (ISSN-L)
- OpenAlex
- W2086254934
- Cited by
- 967
- References
- 23
- Citations by year
- 2026: 20 · 2025: 40 · 2024: 46 · 2023: 57 · 2022: 55 · 2021: 84 · 2020: 71 · 2019: 72 · 2018: 63 · 2017: 61 · 2016: 69 · 2015: 65 · 2014: 52 · 2013: 55 · 2012: 50
- FWCI
- 13.60
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Annual Symposium on Foundations of Computer Science (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Complexity and Algorithms in Graphs
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Graph Theory and Algorithms
- Keywords
- graph cuts, conductance, random walks
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