DBScholar

Back to papers

The Power of Anomaly Detection in Predictive Maintenance: [Experiments & Analysis]

Summary: Large-scale, statistically rigorous TSAD benchmark for online predictive maintenance, comparing algorithms across four implementations, accuracy–runtime trade-offs, and anomaly types. Traditional methods outperform pretrained LLMs, while calibration is crucial for industrial deployment. (summarized by gpt-5.6-luna on Jul 26 2026)

Paper ID
7492
Venue
SIGMOD
Year
2026
Pagerank
5.093636e-05
Overall Rank
10,298 | 29.35%
DOI
10.1145/3802119

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

BibTeX Citation

@inproceedings{papadopoulos_sigmod26,
        title = {{The Power of Anomaly Detection in Predictive Maintenance: [Experiments \& Analysis]}},
        author = {Papadopoulos, Anastasios and Giannoulidis, Apostolos and Gounaris, Anastasios and Paparrizos, John},
        series = {{SIGMOD} '26},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3802119},
        url = {https://dl.acm.org/doi/10.1145/3802119},
        year = {2026}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
10,256 HYDRA: A Multi-Level Hierarchy-Driven Approach for Robust Anomaly Detection in Time Series 2026 SIGMOD 5.093636e-05
10,271 MUFASA: Fast and Accurate Multivariate Time-Series Clustering 2026 SIGMOD 5.093636e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 39 of 39 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
578 Efficient Algorithms for Mining Outliers from Large Data Sets 2000 SIGMOD 0.00016221871
1,029 Anomaly Detection in Time Series: A Comprehensive Evaluation 2022 VLDB 0.00012557065
1,534 Exathlon: A Benchmark for Explainable Anomaly Detection over Time Series 2021 VLDB 0.00010464308
1,579 k-Shape: Efficient and Accurate Clustering of Time Series 2015 SIGMOD 0.00010305183
1,793 TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data 2022 VLDB 9.7435472e-05
1,805 SAND: Streaming Subsequence Anomaly Detection 2021 VLDB 9.7116108e-05
2,004 TSB-UAD: An End-to-End Benchmark Suite for Univariate Time-Series Anomaly Detection 2022 VLDB 9.3207067e-05
2,023 Decomposed Bounded Floats for Fast Compression and Queries 2021 VLDB 9.2950046e-05
2,467 An Efficient and Accurate Method for Evaluating Time Series Similarity 2007 SIGMOD 8.5390765e-05
3,447 Volume Under the Surface: A New Accuracy Evaluation Measure for Time-Series Anomaly Detection 2022 VLDB 7.4085215e-05
3,793 Apache IoTDB: A Time Series Database for IoT Applications 2023 SIGMOD 7.1217835e-05
3,987 Choose Wisely: An Extensive Evaluation of Model Selection for Anomaly Detection in Time Series 2023 VLDB 6.9722766e-05
4,234 GRAIL: Efficient Time-Series Representation Learning 2019 VLDB 6.8171563e-05
4,604 Debunking Four Long-Standing Misconceptions of Time-Series Distance Measures 2020 SIGMOD 6.6104585e-05
5,622 Good to the Last Bit: Data-Driven Encoding with CodecDB 2021 SIGMOD 6.1461066e-05
5,986 AutoTSAD: Unsupervised Holistic Anomaly Detection for Time Series Data 2024 VLDB 6.0183734e-05
6,061 VergeDB: A Database for IoT Analytics on Edge Devices 2021 CIDR 5.9910733e-05
6,356 TimeEval: A Benchmarking Toolkit for Time Series Anomaly Detection Algorithms 2022 VLDB 5.9024453e-05
8,000 PIDS: Attribute Decomposition for Improved Compression and Query Performance in Columnar Storage 2020 VLDB 5.5092344e-05
8,435 Spatial Data Quality in the IoT Era: Management and Exploitation 2022 SIGMOD 5.4253644e-05
9,379 Unsupervised Anomaly Detection in Multivariate Time Series across Heterogeneous Domains 2025 VLDB 5.2755515e-05
9,382 TAB: Unified Benchmarking of Time Series Anomaly Detection Methods 2025 VLDB 5.2755515e-05
9,448 Theseus: Navigating the Labyrinth of Time-Series Anomaly Detection 2022 VLDB 5.2665425e-05
9,477 Odyssey: An Engine Enabling The Time-Series Clustering Journey 2023 VLDB 5.2634238e-05
9,733 SPARTAN: Data-Adaptive Symbolic Time-Series Approximation 2025 SIGMOD 5.227679e-05
10,256 HYDRA: A Multi-Level Hierarchy-Driven Approach for Robust Anomaly Detection in Time Series 2026 SIGMOD 5.093636e-05
10,271 MUFASA: Fast and Accurate Multivariate Time-Series Clustering 2026 SIGMOD 5.093636e-05
10,747 A Structured Study of Multivariate Time-Series Distance Measures 2025 SIGMOD 5.093636e-05
10,796 Understanding the Black Box: A Deep Empirical Dive into Shapley Value Approximations for Tabular Data 2025 SIGMOD 5.093636e-05
10,961 BURST: Rendering Clustering Techniques Suitable for Evolving Streams 2025 VLDB 5.093636e-05
10,977 TSB-AutoAD: Towards Automated Solutions for Time-Series Anomaly Detection 2025 VLDB 5.093636e-05
10,978 Time-Series Clustering: A Comprehensive Study of Data Mining, Machine Learning, and Deep Learning Methods 2025 VLDB 5.093636e-05
10,980 Beyond Compression: A Comprehensive Evaluation of Lossless Floating-Point Compression 2025 VLDB 5.093636e-05
11,056 EasyAD: A Demonstration of Automated Solutions for Time-Series Anomaly Detection 2025 VLDB 5.093636e-05
11,300 Time-Series Anomaly Detection: Overview and New Trends 2024 VLDB 5.093636e-05
13,315 ShapX Engine: A Demonstration of Shapley Value Approximations 2025 SIGMOD -
13,342 SAIL: A Voyage to Symbolic Approximation Solutions for Time-Series Analysis 2025 VLDB -
13,463 SAND in Action: Subsequence Anomaly Detection for Streams 2021 VLDB -
Previous Page 1 / 1 Next

Semantically Similar Papers