Data streams anomaly detection algorithm based on self-set threshold-Reference-Cited by-同舟云学术

Data streams anomaly detection algorithm based on self-set threshold

Published:2018 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 4th International Conference on Communication and Information Processing - ICCIP '18
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Author:

Yuanyan Luo¹,Xuehui Du¹,Yi Sun¹

Affiliation:

1. Information Science and Technology Institute, Zhengzhou, China

Publisher

ACM Press

Reference21 articles.

1. Chandola, Varun, A. Banerjee, and V. Kumar.2009.Anomaly detection: A survey.Acm Computing Surveys41, 3(2009), 1--58.

2. Angiulli, Fabrizio, and F. Fassetti. 2007. Detecting distance-based outliers in streams of data.Sixteenth ACM Conference on Conference on Information and Knowledge ManagementACM (2007), 811--820.

3. Yang, Di, E. A. Rundensteiner, and M. O. Ward.2009. Neighbor-based pattern detection for windows over streaming data.International Conference on Extending Database Technology: Advances in Database TechnologyACM (2009), 529--540.

4. Kontaki, M, et al.2011. Continuous monitoring of distance-based outliers over data streams.IEEE, International Conference on Data EngineeringIEEE (2011), 135--146.

5. Cao, Lei, et al. 2014.Scalable distance-based outlier detection over high-volume data streams.IEEE, International Conference on Data EngineeringIEEE, 2014:76--87.

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