Block Models and Personalized PageRankEIWOS

摘要

Methods for ranking the importance of nodes in a network have a rich history in machine learning and across domains that analyze structured data. Recent work has evaluated these methods through the “seed set expansion problem”: given a subset <mml:math><mml:mi>S</mml:mi></mml:math>S of nodes from a community of interest in an underlying graph, can we reliably identify the rest of the community? We start from the observation that the most widely used techniques for this problem, personalized PageRank and heat kernel methods, operate in...更多

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Volume abs/1607.03483, Issue 1, 2016,

被引用次数27|引用|10
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