A survey of outlier detection in high dimensional data streams

DOI10.1016/j.cosrev.2022.100463OpenAlexW4293242646MaRDI QIDQ2172855

Zaki Brahmi, Mohamed Nazih Omri, Imen Souiden

Publication date: 16 September 2022

Published in: Computer Science Review (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cosrev.2022.100463

zbMATH Keywords

high-dimensional dataoutlier detectiondata streams

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Research exposition (monographs, survey articles) pertaining to computer science (68-02) Computational aspects of data analysis and big data (68T09)

Uses Software

• darch
• Loda
• LOF
• PlanetLab
• Orca

Cites Work

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• Data streams. Models and algorithms.
• Anomaly detection in large-scale data stream networks
• Outlier Analysis
• Reducing the Dimensionality of Data with Neural Networks
• Extensions of Lipschitz mappings into a Hilbert space
• 10.1162/153244303322753616
• Outlier Analysis
• A survey on unsupervised outlier detection in high‐dimensional numerical data
• APPROXIMATE NEAREST NEIGHBOR SEARCH IN HIGH DIMENSIONS
• A survey on concept drift adaptation
• Data Mining
• An outlier mining algorithm based on constrained concept lattice

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