International Conference and School on Network Science

Advances in Network Science pp 1-13 | Cite as

Quad Census Computation: Simple, Efficient, and Orbit-Aware

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9564)

Abstract

The prevalence of select substructures is an indicator of network effects in applications such as social network analysis and systems biology. Moreover, subgraph statistics are pervasive in stochastic network models, and they need to be assessed repeatedly in MCMC sampling and estimation algorithms. We present a new approach to count all induced and non-induced 4-node subgraphs (the quad census) on a per-node and per-edge basis, complete with a separation into their non-automorphic roles in these subgraphs. It is the first approach to do so in a unified manner, and is based on only a clique-listing subroutine. Computational experiments indicate that, despite its simplicity, the approach outperforms previous, less general approaches.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of Computer and Information ScienceUniversity of KonstanzKonstanzGermany

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