Series2Graph: Graph-based Subsequence Anomaly Detection for Time Series
Summary: Unsupervised, domain-agnostic subsequence anomaly detection for time series. Series2Graph forms a graph on a low-dimensional subsequence embedding to detect single and recurrent anomalies of varying length, without labels, and outperforms baselines in accuracy and speed. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Paul Boniol (Electricite de France; Universite de Paris)
- 2. Themis Palpanas (French University Institute; Universite de Paris)
BibTeX Citation
@article{boniol_vldb20,
title = {{Series2Graph: Graph-based Subsequence Anomaly Detection for Time Series}},
author = {Boniol, Paul and Palpanas, Themis},
journal = {PVLDB},
series = {{VLDB} '20},
volume = {13},
number = {11},
pages = {1821--1834},
doi = {10.14778/3407790.3407792},
url = {https://doi.org/10.14778/3407790.3407792},
year = {2020}
}
Incoming Citations (Sorted by Pagerank)
Showing 27 of 27 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 142 | LOF: Identifying Density-Based Local Outliers | 2000 | SIGMOD | 0.0002962566 |
| 148 | Gorilla: A Fast, Scalable, In-Memory Time Series Database | 2015 | VLDB | 0.00029250767 |
| 2,340 | Online Outlier Detection in Sensor Data Using Non-Parametric Models | 2006 | VLDB | 8.7246796e-05 |
| 2,734 | Return of the Lernaean Hydra: Experimental Evaluation of Data Series Approximate Similarity Search | 2020 | VLDB | 8.190416e-05 |
| 3,037 | The Lernaean Hydra of Data Series Similarity Search: An Experimental Evaluation of the State of the Art | 2019 | VLDB | 7.8275859e-05 |
| 4,212 | Data Series Progressive Similarity Search with Probabilistic Quality Guarantees | 2020 | SIGMOD | 6.8283344e-05 |
| 6,109 | GraphAn: Graph-based Subsequence Anomaly Detection | 2020 | VLDB | 5.9730493e-05 |
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|---|---|---|---|---|
| 1 | 6,356 | TimeEval: A Benchmarking Toolkit for Time Series Anomaly Detection Algorithms | 2022 | VLDB |
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| 4 | 11,099 | MLP-Mixer based Masked Autoencoders Are Effective, Explainable and Robust for Time Series Anomaly Detection | 2025 | VLDB |
| 5 | 8,229 | Mining Approximate Top-K Subspace Anomalies in Multi-Dimensional Time-Series Data | 2007 | VLDB |
| 6 | 11,300 | Time-Series Anomaly Detection: Overview and New Trends | 2024 | VLDB |
| 7 | 5,986 | AutoTSAD: Unsupervised Holistic Anomaly Detection for Time Series Data | 2024 | VLDB |
| 8 | 6,141 | An Experimental Evaluation of Anomaly Detection in Time Series | 2024 | VLDB |
| 9 | 1,029 | Anomaly Detection in Time Series: A Comprehensive Evaluation | 2022 | VLDB |
| 10 | 6,109 | GraphAn: Graph-based Subsequence Anomaly Detection | 2020 | VLDB |