Time-Series Clustering: A Comprehensive Study of Data Mining, Machine Learning, and Deep Learning Methods

Summary: Benchmarks 84 time-series clustering methods across 10 classes and 128 datasets with rigorous statistics, reproducibility checks, and scalability analysis. Finds no significant improvement over decade-old k-Shape, challenging deep/foundation-model claims while identifying promising DL. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID: 14240
Venue: VLDB
Year: 2025
Pagerank: 5.093636e-05
Overall Rank: 10,978 | 24.69%
DOI: 10.14778/3749646.3749700

Incoming Non-self Citations Over Time

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

Authors

1. John Paparrizos (Aristotle University of Thessaloniki; Ohio State University)
2. Sai Prasanna Teja Reddy Bogireddy (Exelon Utilities)

BibTeX Citation

@article{paparrizos_vldb25,
        title = {{Time-Series Clustering: A Comprehensive Study of Data Mining, Machine Learning, and Deep Learning Methods}},
        author = {Paparrizos, John and Bogireddy, Sai Prasanna Teja Reddy},
        journal = {PVLDB},
        series = {{VLDB} '25},
        volume = {18},
        number = {11},
        pages = {4380--4395},
        doi = {10.14778/3749646.3749700},
        url = {https://doi.org/10.14778/3749646.3749700},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

Showing 6 of 6 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
10,298	The Power of Anomaly Detection in Predictive Maintenance: [Experiments & Analysis]	2026	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
10,980	Beyond Compression: A Comprehensive Evaluation of Lossless Floating-Point Compression	2025	VLDB	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 21 of 21 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
221	Robust and Fast Similarity Search for Moving Object Trajectories	2005	SIGMOD	0.00024224879
291	OPTICS: Ordering Points To Identify the Clustering Structure	1999	SIGMOD	0.00022264197
303	On The Marriage of Lp-norms and Edit Distance	2004	VLDB	0.00021956234
1,722	Indexable PLA for Efficient Similarity Search	2007	VLDB	9.9227051e-05
1,805	SAND: Streaming Subsequence Anomaly Detection	2021	VLDB	9.7116108e-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
3,486	Scalable, Variable-Length Similarity Search in Data Series: The ULISSE Approach	2018	VLDB	7.3696676e-05
3,987	Choose Wisely: An Extensive Evaluation of Model Selection for Anomaly Detection in Time Series	2023	VLDB	6.9722766e-05
4,151	YADING: Fast Clustering of Large-Scale Time Series Data	2015	VLDB	6.8703273e-05
5,244	Top-k Nearest Neighbor Search In Uncertain Data Series	2015	VLDB	6.3018164e-05
5,325	Rare Time Series Motif Discovery from Unbounded Streams	2015	VLDB	6.2641987e-05
5,622	Good to the Last Bit: Data-Driven Encoding with CodecDB	2021	SIGMOD	6.1461066e-05
8,000	PIDS: Attribute Decomposition for Improved Compression and Query Performance in Columnar Storage	2020	VLDB	5.5092344e-05
8,159	FeatTS: Feature-based Time Series Clustering	2021	SIGMOD	5.4756587e-05
9,448	Theseus: Navigating the Labyrinth of Time-Series Anomaly Detection	2022	VLDB	5.2665425e-05
9,733	SPARTAN: Data-Adaptive Symbolic Time-Series Approximation	2025	SIGMOD	5.227679e-05
10,747	A Structured Study of Multivariate Time-Series Distance Measures	2025	SIGMOD	5.093636e-05
10,961	BURST: Rendering Clustering Techniques Suitable for Evolving Streams	2025	VLDB	5.093636e-05
10,980	Beyond Compression: A Comprehensive Evaluation of Lossless Floating-Point Compression	2025	VLDB	5.093636e-05
13,463	SAND in Action: Subsequence Anomaly Detection for Streams	2021	VLDB	-

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