Modeling and detecting change in temporal networks via the degree corrected stochastic block model-Reference-Cited by-同舟云学术

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Modeling and detecting change in temporal networks via the degree corrected stochastic block model

Published:2019-07 Issue:5 Volume:35 Page:1363-1378
ISSN:0748-8017
Container-title:Quality and Reliability Engineering International
language:en
Short-container-title:Qual Reliab Engng Int

Author:

Wilson James D.¹^ORCID,Stevens Nathaniel T.²^ORCID,Woodall William H.³

Affiliation:

1. Department of Mathematics and Statistics University of San Francisco San Francisco California

2. Department of Statistics and Actuarial Sciences University of Waterloo Waterloo Ontario Canada

3. Department of Statistics Virginia Tech Blacksburg Virginia

Funder

Division of Mathematical Sciences

Publisher

Wiley

Subject

Management Science and Operations Research,Safety, Risk, Reliability and Quality

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/qre.2520

Reference63 articles.

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2. ShettyJ AdibiJ.Discovering important nodes through graph entropy the case of Enron email database. In: Proceedings of the 3rd international workshop on link discovery ACM;2005;New York NY USA:74‐81.

3. AkogluL FaloutsosC.Anomaly event and fraud detection in large network datasets. In: WSDM '13 Proceedings of the sixth ACM international conference on Web search and data mining ACM;2013;New York NY USA:773‐774.

4. PanditS ChauDH WangS FaloutsosC.Netprobe: a fast and scalable system for fraud detection in online auction networks. In: Proceedings of the 16th international conference on world wide web ACM;2007;Raleigh NC:201‐210.

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