Advances in Time-Series Anomaly Detection: Algorithms, Benchmarks, and Evaluation Measures

Authors

Paul Boniol (ORCID: https://orcid.org/0000-0001-8516-0123)
Themis Palpanas (ORCID: https://orcid.org/0000-0002-8031-0265)
Qinghua Liu (ORCID: https://orcid.org/0000-0003-2914-3075)
John Paparrizos (ORCID: https://orcid.org/0000-0002-7592-748X)

Institutions

Centre National de la Recherche Scientifique (FR)
Institut national de recherche en sciences et technologies du numérique (FR)
Université Paris Cité (FR)
Aristotle University of Thessaloniki (GR)
École Normale Supérieure - PSL (FR)
Sorbonne Paris Cité (FR)
The Ohio State University (US)

Publication Details

Published: 2025-08-03
DOI: https://doi.org/10.1145/3711896.3736565
Citations: 8
Primary Topic: Anomaly Detection Techniques and Applications
Type: article
Field-Weighted Citation Impact: 19.85

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article

Advances in Time-Series Anomaly Detection: Algorithms, Benchmarks, and Evaluation Measures

Paul Boniol, Themis Palpanas, Qinghua Liu, John Paparrizos

Aug 3, 2025

8 citations

Anomaly Detection Techniques and Applications

19.85

article

Advances in Time-Series Anomaly Detection: Algorithms, Benchmarks, and Evaluation Measures

Paul Boniol, Themis Palpanas, Qinghua Liu, John Paparrizos

August 3, 2025article en

8 citations

Abstract

No abstract available for this paper.

Centre National de la Recherche Scientifique (FR), Institut national de recherche en sciences et technologies du numérique (FR), Université Paris Cité (FR), Aristotle University of Thessaloniki (GR), École Normale Supérieure - PSL (FR), Sorbonne Paris Cité (FR), The Ohio State University (US)

Openalex Percentile: Top 1%

Anomaly Detection Techniques and Applications

19.85

DOI Open Access PDF OpenAlex

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