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Communication Dans Un Congrès Année : 2024

An Interactive Dive into Time-Series Anomaly Detection

Résumé

Anomaly detection is an important problem in data analytics with applications in many domains. In recent years, there has been an increasing interest in anomaly detection tasks applied to time series. In this tutorial, we take a holistic view of anomaly detection in time series, starting from the core definitions and taxonomies related to time series and anomaly types, to an extensive description of the anomaly detection methods proposed by different communities in the literature. We explore the literature and the proposed methods by demonstrating systems that help users understand the core computational steps of some methods and navigate benchmark results. Finally, we describe the problem of model selection for anomaly detection and discuss recent experimental results.
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Dates et versions

hal-04590244 , version 1 (28-05-2024)

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  • HAL Id : hal-04590244 , version 1

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Paul Boniol, John Paparrizos, Themis Palpanas. An Interactive Dive into Time-Series Anomaly Detection. ICDE 2024 - 40th International Conference on Data Engineering, May 2024, Utrecht, Netherlands. ⟨hal-04590244⟩
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