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Odyssey: An Engine Enabling The Time-Series Clustering Journey

Summary: Odyssey is a modular web engine that rigorously benchmarks 80 time‑series clustering methods across 9 classes on 128 diverse datasets. It exposes overlooked high-performing classes, challenges elastic-distance and deep‑learning claims, and finds no method significantly outperforming k‑Shape. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
h97c737ccd89b60f5
Venue
VLDB
Year
2023
Pagerank
5.1453267e-05
Overall Rank
9,658 | 35.07%
DOI
10.14778/3611540.3611622

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{paparrizos_vldb23,
        title = {{Odyssey: An Engine Enabling The Time-Series Clustering Journey}},
        author = {Paparrizos, John and Reddy, Sai Prasanna Teja},
        journal = {PVLDB},
        series = {{VLDB} '23},
        volume = {16},
        number = {12},
        pages = {4066--4069},
        doi = {10.14778/3611540.3611622},
        url = {https://doi.org/10.14778/3611540.3611622},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 11 of 11 citing papers.

Rank Citing Paper Year Venue Pagerank
7,641 A Structured Study of Multivariate Time-Series Distance Measures 2025 SIGMOD 5.4772833e-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
9,909 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
10,510 The Power of Anomaly Detection in Predictive Maintenance: [Experiments & Analysis] 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
11,594 DARKER: Efficient Transformer with Data-driven Attention Mechanism for Time Series 2024 VLDB 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 13 of 13 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
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
1,937 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
3,298 Volume Under the Surface: A New Accuracy Evaluation Measure for Time-Series Anomaly Detection 2022 VLDB 7.4447462e-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
5,471 Good to the Last Bit: Data-Driven Encoding with CodecDB 2021 SIGMOD 6.1181669e-05
6,189 VergeDB: A Database for IoT Analytics on Edge Devices 2021 CIDR 5.8568233e-05
8,160 PIDS: Attribute Decomposition for Improved Compression and Query Performance in Columnar Storage 2020 VLDB 5.3871591e-05
9,626 Theseus: Navigating the Labyrinth of Time-Series Anomaly Detection 2022 VLDB 5.1483755e-05
11,749 Accelerating Similarity Search for Elastic Measures: A Study and New Generalization of Lower Bounding Distances 2023 VLDB 4.9793485e-05
13,777 SAND in Action: Subsequence Anomaly Detection for Streams 2021 VLDB -
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