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
h5131bf8b22025cbe
Venue
SIGMOD
Year
2026
Pagerank
4.9793485e-05
Overall Rank
10,510 | 29.34%
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
10,469 HYDRA: A Multi-Level Hierarchy-Driven Approach for Robust Anomaly Detection in Time Series 2026 SIGMOD 4.9793485e-05
10,483 MUFASA: Fast and Accurate Multivariate Time-Series Clustering 2026 SIGMOD 4.9793485e-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 0.00029202746
583 Efficient Algorithms for Mining Outliers from Large Data Sets 2000 SIGMOD 0.00015960125
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
1,579 k-Shape: Efficient and Accurate Clustering of Time Series 2015 SIGMOD 0.00010186397
1,629 SAND: Streaming Subsequence Anomaly Detection 2021 VLDB 0.00010036401
1,740 TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data 2022 VLDB 9.7439205e-05
1,937 TSB-UAD: An End-to-End Benchmark Suite for Univariate Time-Series Anomaly Detection 2022 VLDB 9.3387043e-05
1,973 Decomposed Bounded Floats for Fast Compression and Queries 2021 VLDB 9.2834606e-05
2,494 An Efficient and Accurate Method for Evaluating Time Series Similarity 2007 SIGMOD 8.3888883e-05
3,298 Volume Under the Surface: A New Accuracy Evaluation Measure for Time-Series Anomaly Detection 2022 VLDB 7.4447462e-05
3,622 Apache IoTDB: A Time Series Database for IoT Applications 2023 SIGMOD 7.1536644e-05
3,726 Choose Wisely: An Extensive Evaluation of Model Selection for Anomaly Detection in Time Series 2023 VLDB 7.0701368e-05
4,316 GRAIL: Efficient Time-Series Representation Learning 2019 VLDB 6.6683448e-05
4,703 Debunking Four Long-Standing Misconceptions of Time-Series Distance Measures 2020 SIGMOD 6.4621968e-05
5,115 TimeEval: A Benchmarking Toolkit for Time Series Anomaly Detection Algorithms 2022 VLDB 6.2679451e-05
5,471 Good to the Last Bit: Data-Driven Encoding with CodecDB 2021 SIGMOD 6.1181669e-05
6,073 AutoTSAD: Unsupervised Holistic Anomaly Detection for Time Series Data 2024 VLDB 5.8953069e-05
6,189 VergeDB: A Database for IoT Analytics on Edge Devices 2021 CIDR 5.8568233e-05
7,094 Time-Series Clustering: A Comprehensive Study of Data Mining, Machine Learning, and Deep Learning Methods 2025 VLDB 5.601767e-05
7,641 A Structured Study of Multivariate Time-Series Distance Measures 2025 SIGMOD 5.4772833e-05
7,877 Spatial Data Quality in the IoT Era: Management and Exploitation 2022 SIGMOD 5.4346692e-05
8,160 PIDS: Attribute Decomposition for Improved Compression and Query Performance in Columnar Storage 2020 VLDB 5.3871591e-05
9,482 TSB-AutoAD: Towards Automated Solutions for Time-Series Anomaly Detection 2025 VLDB 5.1708619e-05
9,483 Beyond Compression: A Comprehensive Evaluation of Lossless Floating-Point Compression 2025 VLDB 5.1708619e-05
9,488 Time-Series Anomaly Detection: Overview and New Trends 2024 VLDB 5.1708619e-05
9,564 Unsupervised Anomaly Detection in Multivariate Time Series across Heterogeneous Domains 2025 VLDB 5.1571823e-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
9,658 Odyssey: An Engine Enabling The Time-Series Clustering Journey 2023 VLDB 5.1453267e-05
9,909 SPARTAN: Data-Adaptive Symbolic Time-Series Approximation 2025 SIGMOD 5.1103839e-05
10,469 HYDRA: A Multi-Level Hierarchy-Driven Approach for Robust Anomaly Detection in Time Series 2026 SIGMOD 4.9793485e-05
10,483 MUFASA: Fast and Accurate Multivariate Time-Series Clustering 2026 SIGMOD 4.9793485e-05
11,211 Understanding the Black Box: A Deep Empirical Dive into Shapley Value Approximations for Tabular Data 2025 SIGMOD 4.9793485e-05
11,348 BURST: Rendering Clustering Techniques Suitable for Evolving Streams 2025 VLDB 4.9793485e-05
11,419 EasyAD: A Demonstration of Automated Solutions for Time-Series Anomaly Detection 2025 VLDB 4.9793485e-05
13,637 ShapX Engine: A Demonstration of Shapley Value Approximations 2025 SIGMOD -
13,660 SAIL: A Voyage to Symbolic Approximation Solutions for Time-Series Analysis 2025 VLDB -
13,777 SAND in Action: Subsequence Anomaly Detection for Streams 2021 VLDB -
Previous Page 1 / 1 Next

Semantically Similar Papers