Fast and Scalable Mining of Time Series Motifs with Probabilistic Guarantees
Summary: Fast, scalable top-k time-series motif mining with probabilistic guarantees via LSH and self-tuning. Correctness proofs and cost bounds; optimizations prune distance computations; CPU-scale experiments show billion-point data processed with speedups. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Matteo Ceccarello (Free University of Bozen/Bolzano)
- 2. Johann Gamper (Free University of Bozen/Bolzano)
BibTeX Citation
@article{ceccarello_vldb22,
title = {{Fast and Scalable Mining of Time Series Motifs with Probabilistic Guarantees}},
author = {Ceccarello, Matteo and Gamper, Johann},
journal = {PVLDB},
series = {{VLDB} '22},
volume = {15},
number = {13},
pages = {3841--3853},
doi = {10.14778/3565838.3565840},
url = {https://doi.org/10.14778/3565838.3565840},
year = {2022}
}Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,099 | Time Series Data Mining: A Unifying View | 2023 | VLDB | 5.601767e-05 |
| 8,026 | TSM-Bench: Benchmarking Time Series Database Systems for Monitoring Applications | 2023 | VLDB | 5.4045222e-05 |
| 11,262 | Time Series Motif Discovery: A Comprehensive Evaluation | 2025 | VLDB | 4.9793485e-05 |
| 11,318 | MOMENTI: Scalable Motif Mining in Multidimensional Time Series | 2025 | VLDB | 4.9793485e-05 |
| 11,581 | Efficient Discovery of Significant Patterns with Few-Shot Resampling | 2024 | VLDB | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 829 | Similarity-Based Queries for Time Series Data | 1997 | SIGMOD | 0.00013611445 |
| 1,792 | Fast Approximate Correlation for Massive Time-series Data | 2010 | SIGMOD | 9.6238255e-05 |
| 2,568 | Locality-Sensitive Hashing for Earthquake Detection: A Case Study of Scaling Data-Driven Science | 2018 | VLDB | 8.2870435e-05 |
| 3,257 | VALMOD: A Suite for Easy and Exact Detection of Variable Length Motifs in Data Series | 2018 | SIGMOD | 7.4874916e-05 |
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