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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)

Paper ID
hca29f7e2ce0c81c7
Venue
VLDB
Year
2020
Pagerank
8.555841e-05
Overall Rank
2,375 | 84.04%
DOI
10.14778/3407790.3407792

Incoming Non-self Citations Over Time

Authors

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.

Rank Citing Paper Year Venue Pagerank
1,005 Anomaly Detection in Time Series: A Comprehensive Evaluation 2022 VLDB 0.00012590067
1,544 Exathlon: A Benchmark for Explainable Anomaly Detection over Time Series 2021 VLDB 0.00010304574
1,629 SAND: Streaming Subsequence Anomaly Detection 2021 VLDB 0.00010036401
1,937 TSB-UAD: An End-to-End Benchmark Suite for Univariate Time-Series Anomaly Detection 2022 VLDB 9.3387043e-05
2,265 ELPIS: Graph-Based Similarity Search for Scalable Data Science 2023 VLDB 8.7238222e-05
2,871 Graph-Based Vector Search: An Experimental Evaluation of the State-of-the-Art 2025 SIGMOD 7.9229231e-05
3,298 Volume Under the Surface: A New Accuracy Evaluation Measure for Time-Series Anomaly Detection 2022 VLDB 7.4447462e-05
3,726 Choose Wisely: An Extensive Evaluation of Model Selection for Anomaly Detection in Time Series 2023 VLDB 7.0701368e-05
4,304 Data Series Progressive Similarity Search with Probabilistic Quality Guarantees 2020 SIGMOD 6.6771697e-05
5,559 ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly Detection 2024 VLDB 6.0849722e-05
6,197 GraphAn: Graph-based Subsequence Anomaly Detection 2020 VLDB 5.8527203e-05
6,609 Dumpy: A Compact and Adaptive Index for Large Data Series Collections 2023 SIGMOD 5.7354155e-05
8,400 TOD: GPU-accelerated Outlier Detection via Tensor Operations 2023 VLDB 5.3395906e-05
9,440 Odyssey: A Journey in the Land of Distributed Data Series Similarity Search 2023 VLDB 5.1771634e-05
9,482 TSB-AutoAD: Towards Automated Solutions for Time-Series Anomaly Detection 2025 VLDB 5.1708619e-05
9,567 TAB: Unified Benchmarking of Time Series Anomaly Detection Methods 2025 VLDB 5.1571823e-05
9,626 Theseus: Navigating the Labyrinth of Time-Series Anomaly Detection 2022 VLDB 5.1483755e-05
9,660 dCAM: Dimension-wise Class Activation Map for Explaining Multivariate Data Series Classification 2022 SIGMOD 5.1453267e-05
10,469 HYDRA: A Multi-Level Hierarchy-Driven Approach for Robust Anomaly Detection in Time Series 2026 SIGMOD 4.9793485e-05
11,053 Efficient Partition-based Approaches for Diversified Top-k Subgraph Matching 2026 VLDB 4.9793485e-05
11,249 Streaming Time Series Subsequence Anomaly Detection: A Glance and Focus Approach 2025 VLDB 4.9793485e-05
11,363 DIM-SUM: Dynamic Imputation for Smart Utility Management 2025 VLDB 4.9793485e-05
11,451 MLP-Mixer based Masked Autoencoders Are Effective, Explainable and Robust for Time Series Anomaly Detection 2025 VLDB 4.9793485e-05
11,717 LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation 2023 SIGMOD 4.9793485e-05
11,749 Accelerating Similarity Search for Elastic Measures: A Study and New Generalization of Lower Bounding Distances 2023 VLDB 4.9793485e-05
12,003 Comprehensible Counterfactual Explanation on Kolmogorov-Smirnov Test 2021 VLDB 4.9793485e-05
13,777 SAND in Action: Subsequence Anomaly Detection for Streams 2021 VLDB -
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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.

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