A physical model for efficient ranking in networks
Abstract
We present a physically inspired model and an efficient algorithm to infer hierarchical rankings of nodes in directed networks. It assigns real-valued ranks to nodes rather than simply ordinal ranks, and it formalizes the assumption that interactions are more likely to occur between individuals with similar ranks. It provides a natural statistical significance test for the inferred hierarchy, and it can be used to perform inference tasks such as...
Paper Details
Title
A physical model for efficient ranking in networks
Published Date
Jul 6, 2018
Journal
Volume
4
Issue
7
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