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An Edge-Centric Approach for Change Point Detection in Dynamic Networks

  • Yongsheng ChengEmail author
  • Xiaokang Lin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8643)

Abstract

The graph-theoretic analysis of dynamic networks has attracted much research interests recently. Change point detection is essential to understand the dynamic structure of time evolving networks. This work proposes an edge-centric approach to detect the change points of dynamic networks. In the proposed method, a singular value decomposition (SVD) is performed on a newly defined edge-segment matrix and the decomposition is projected to a lower dimensional latent space. Then the dissimilarity between graph segments is calculated for detecting the change points. The approach applies to directed/undirected and weighted/unweighted dynamic graphs. Experiments are conducted on both a synthetic dataset and the Enron email dataset. Results show that change points of the dynamic networks are effectively detected by the proposed approach.

Keywords

Change point detection Dynamic networks Graph segments Latent semantic analysis 

Notes

Acknowledgments

This work was partly supported by the Tsinghua-Qualcomm Joint Research Program.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.State Key Laboratory on Microwave and Digital Communications, Tsinghua National Laboratory for Information Science and Technology, Department of Electronic EngineeringTsinghua UniversityBeijingChina

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