The heat kernel is a type of graph diffusion that, like the much-used personalized PageRank diffusion, is useful in identifying a community nearby a starting seed node. We present the firstâ€¦ (More)

We consider stochastic transition matrices from large social and information networks. For these matrices, we describe and evaluate three fast methods to estimate one column of the matrixâ€¦ (More)

Personalized PageRank vectors used for many community detection and graph diffusion problems have a subtle dependence on a parameter epsilon that controls their accuracy. This parameter governs theâ€¦ (More)

We study the behaviour of network diffusions based on the PageRank random walk from a set of seed nodes. These diffusions are known to reveal small, localized clusters (or communities), and alsoâ€¦ (More)

We consider random-walk transition matrices from large social and information networks. For these matrices, we describe and evaluate a fast method to estimate one column of the matrix exponential.â€¦ (More)

The personalized PageRank diffusion is a fundamental tool in network analysis tasks like community detection and link prediction. This tool models the spread of a quantity from a small, initial setâ€¦ (More)

Local community detection, the problem of identifying a set of relevant nodes nearby a small set of input seed nodes, is an important graph primitive with a wealth of applications and researchâ€¦ (More)

Large graphs arise in a number of contexts and understanding their structure and extracting information from them is an important research area. Early algorithms for mining communities have focusedâ€¦ (More)

Identifying communities plays a central role in understanding the structure of large networks. As practitioners analyze progressively larger networks, it becomes increasingly important to understandâ€¦ (More)