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Personalized PageRank based Community Detection

Personalized PageRank based Community Detection

This video was recorded at 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Chicago 2013. Personalized PageRank is a reasonably well known technique to find a community in a network starting from a single node. It works by approximating the stationary distribution of a resetting random-walk and using that stationary distribution to estimate the presence of nearby cuts in the graph. I'll discuss recent work on how to find use a personalized PageRank community to quickly estimate the sets of best conductance anywhere in the graph as well as how to find a good set of seeds to cover the entire graph with personalized PageRank communities.


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