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Uncovering the Small Community Structure in Large Networks: A Local Spectral Approach
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BibTeX
@MISC{Li_uncoveringthe,
author = {Yixuan Li and Kun He and David Bindel and John E. Hopcroft},
title = {Uncovering the Small Community Structure in Large Networks: A Local Spectral Approach},
year = {}
}
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Abstract
Large graphs arise in a number of contexts and understand-ing their structure and extracting information from them is an important research area. Early algorithms on mining communities have focused on the global structure, and of-ten run in time functional to the size of the entire graph. Nowadays, as we often explore networks with billions of ver-tices and find communities of size hundreds, it is crucial to shift our attention from macroscopic structure to micro-scopic structure when dealing with large networks. A grow-ing body of work has been adopting local expansion methods in order to identify the community from a few exemplary seed members. In this paper, we propose a novel approach for finding overlapping communities called LEMON (Local Expansion
Keyphrases
large network small community structure local spectral approach local expansion method entire graph macroscopic structure important research area local expansion large graph exemplary seed member of-ten run global structure size hundred novel approach mining community grow-ing body early algorithm micro-scopic structure
