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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
- 12082
- Venue
- VLDB
- Year
- 2020
- Pagerank
- 8.3832357e-05
- Overall Rank
- 2,644 | 81.61%
- DOI
-
10.14778/3407790.3407792
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 26 of 26 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 1,253 |
Anomaly Detection in Time Series: A Comprehensive Evaluation |
2022 |
VLDB |
0.00013032074 |
| 1,634 |
Exathlon: A Benchmark for Explainable Anomaly Detection over Time Series |
2021 |
VLDB |
0.00011058945 |
| 2,029 |
SAND: Streaming Subsequence Anomaly Detection |
2021 |
VLDB |
9.740868e-05 |
| 2,381 |
TSB-UAD: An End-to-End Benchmark Suite for Univariate Time-Series Anomaly Detection |
2022 |
VLDB |
8.9327638e-05 |
| 3,400 |
ELPIS: Graph-Based Similarity Search for Scalable Data Science |
2023 |
VLDB |
7.1405533e-05 |
| 3,943 |
Volume Under the Surface: A New Accuracy Evaluation Measure for Time-Series Anomaly Detection |
2022 |
VLDB |
6.6099833e-05 |
| 4,079 |
Choose Wisely: An Extensive Evaluation of Model Selection for Anomaly Detection in Time Series |
2023 |
VLDB |
6.4663636e-05 |
| 4,536 |
Data Series Progressive Similarity Search with Probabilistic Quality Guarantees |
2020 |
SIGMOD |
6.104642e-05 |
| 4,731 |
Graph-Based Vector Search: An Experimental Evaluation of the State-of-the-Art |
2025 |
SIGMOD |
5.966659e-05 |
| 5,777 |
ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly Detection |
2024 |
VLDB |
5.3308813e-05 |
| 6,116 |
GraphAn: Graph-based Subsequence Anomaly Detection |
2020 |
VLDB |
5.2039218e-05 |
| 7,095 |
Dumpy: A Compact and Adaptive Index for Large Data Series Collections |
2023 |
SIGMOD |
4.8350023e-05 |
| 8,157 |
TOD: GPU-accelerated Outlier Detection via Tensor Operations |
2023 |
VLDB |
4.5730908e-05 |
| 9,206 |
Odyssey: A Journey in the Land of Distributed Data Series Similarity Search |
2023 |
VLDB |
4.373492e-05 |
| 9,294 |
Theseus: Navigating the Labyrinth of Time-Series Anomaly Detection |
2022 |
VLDB |
4.3608061e-05 |
| 9,331 |
dCAM: Dimension-wise Class Activation Map for Explaining Multivariate Data Series Classification |
2022 |
SIGMOD |
4.3556432e-05 |
| 10,308 |
Efficient Partition-based Approaches for Diversified Top-k Subgraph Matching |
2026 |
VLDB |
4.1945683e-05 |
| 10,579 |
Streaming Time Series Subsequence Anomaly Detection: A Glance and Focus Approach |
2025 |
VLDB |
4.1945683e-05 |
| 10,637 |
TAB: Unified Benchmarking of Time Series Anomaly Detection Methods |
2025 |
VLDB |
4.1945683e-05 |
| 10,738 |
TSB-AutoAD: Towards Automated Solutions for Time-Series Anomaly Detection |
2025 |
VLDB |
4.1945683e-05 |
| 10,744 |
DIM-SUM: Dynamic IMputation for Smart Utility Management |
2025 |
VLDB |
4.1945683e-05 |
| 10,876 |
MLP-Mixer based Masked Autoencoders Are Effective, Explainable and Robust for Time Series Anomaly Detection |
2025 |
VLDB |
4.1945683e-05 |
| 11,200 |
LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation |
2023 |
SIGMOD |
4.1945683e-05 |
| 11,235 |
Accelerating Similarity Search for Elastic Measures: A Study and New Generalization of Lower Bounding Distances |
2023 |
VLDB |
4.1945683e-05 |
| 11,500 |
Comprehensible Counterfactual Explanation on Kolmogorov-Smirnov Test |
2021 |
VLDB |
4.1945683e-05 |
| 13,261 |
SAND in Action: Subsequence Anomaly Detection for Streams |
2021 |
VLDB |
- |
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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| Overall Rank |
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Year |
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| 7,182 |
TimeEval: A Benchmarking Toolkit for Time Series Anomaly Detection Algorithms |
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4.8072409e-05 |
| 13,261 |
SAND in Action: Subsequence Anomaly Detection for Streams |
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VLDB |
- |
| 10,579 |
Streaming Time Series Subsequence Anomaly Detection: A Glance and Focus Approach |
2025 |
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4.1945683e-05 |
| 10,876 |
MLP-Mixer based Masked Autoencoders Are Effective, Explainable and Robust for Time Series Anomaly Detection |
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4.1945683e-05 |
| 8,228 |
Mining Approximate Top-K Subspace Anomalies in Multi-Dimensional Time-Series Data |
2007 |
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4.5549459e-05 |
| 11,094 |
Time-Series Anomaly Detection: Overview and New Trends |
2024 |
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4.1945683e-05 |
| 6,423 |
AutoTSAD: Unsupervised Holistic Anomaly Detection for Time Series Data |
2024 |
VLDB |
5.0670573e-05 |
| 6,440 |
An Experimental Evaluation of Anomaly Detection in Time Series |
2024 |
VLDB |
5.0603878e-05 |
| 1,253 |
Anomaly Detection in Time Series: A Comprehensive Evaluation |
2022 |
VLDB |
0.00013032074 |
| 6,116 |
GraphAn: Graph-based Subsequence Anomaly Detection |
2020 |
VLDB |
5.2039218e-05 |