Abstract
A local partitioning algorithm finds a set with small conductance near a specified seed vertex. In this paper, we present a generalization of a local partitioning algorithm for undirected graphs to strongly connected directed graphs. In particular, we prove that by computing a personalized PageRank vector in a directed graph, starting from a single seed vertex within a set S that has conductance at most α, and by performing a sweep over that vector, we can obtain a set of vertices S′ with conductance \(\Phi_{M}(S')= O(\sqrt{\alpha \log |S|})\). Here, the conductance function Φ M is defined in terms of the stationary distribution of a random walk in the directed graph. In addition, we describe how this algorithm may be applied to the PageRank Markov chain of an arbitrary directed graph, which provides a way to partition directed graphs that are not strongly connected.
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Andersen, R., Chung, F., Lang, K. (2007). Local Partitioning for Directed Graphs Using PageRank. In: Bonato, A., Chung, F.R.K. (eds) Algorithms and Models for the Web-Graph. WAW 2007. Lecture Notes in Computer Science, vol 4863. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77004-6_13
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DOI: https://doi.org/10.1007/978-3-540-77004-6_13
Publisher Name: Springer, Berlin, Heidelberg
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