Parallel algorithms for anomalous subgraph detection-Reference-Cited by-同舟云学术

Parallel algorithms for anomalous subgraph detection

Published:2016-01-28 Issue:3 Volume:29 Page:e3769
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat.: Pract. Exper.

Author:

Zhao Jieyu¹,Li Jianxin¹,Zhou Baojian²,Chen Feng²,Tomchik Paul²,Ju Wuyang¹

Affiliation:

1. State Key Laboratory of Software Development Environment; Beihang University; Beijing China

2. College of Engineering and Applied Sciences; University at Albany, SUNY; Albany NY USA

Funder

NSFC Program

Ministry of Science and Technology of the People's Republic of China

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/cpe.3769/fullpdf

Reference28 articles.

1. Singh N Miller BA Bliss NT Wolfe PJ Anomalous subgraph detection via sparse principal component analysis 2011 IEEE Statistical Signal Processing Workshop (SSP) IEEE Nice, France 2011 485 488

2. Miller B Bliss N Wolfe PJ Subgraph detection using eigenvector l1 norms Advances in Neural Information Processing Systems Vancouver, Canada 2010 1633 1641

3. Chen F Neill DB Non-parametric scan statistics for event detection and forecasting in heterogeneous social media graphs Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining ACM New York City 2014 1166 1175

4. Bogdanov P Mongiovi M Singh AK Mining heavy subgraphs in time-evolving networks 2011 IEEE 11th International Conference on Data Mining (ICDM) IEEE Vancouver, Canada 2011 81 90

5. Changepoint detection over graphs with the spectral scan statistic;Sharpnack;arXiv preprint arXiv:1206.0773,2012

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Co-Membership-based Generic Anomalous Communities Detection;Neural Processing Letters;2023-01-05

2. MASA: An efficient framework for anomaly detection in multi-attributed networks;Computers & Security;2021-03

3. MIDAS: Multilinear detection at scale;Journal of Parallel and Distributed Computing;2019-10

4. A coordination polymer-derived Co3O4/Co–N@NMC composite material as a Zn–air battery cathode electrocatalyst and microwave absorber;Dalton Transactions;2019

5. A possibilistic framework for the detection of terrorism‐related Twitter communities in social media;Concurrency and Computation: Practice and Experience;2018-11-28