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 |
|---|---|---|---|---|
| 6,959 | Time Series Data Mining: A Unifying View | 2023 | VLDB | 5.7303405e-05 |
| 8,959 | TSM-Bench: Benchmarking Time Series Database Systems for Monitoring Applications | 2023 | VLDB | 5.3444909e-05 |
| 10,859 | Time Series Motif Discovery: A Comprehensive Evaluation | 2025 | VLDB | 5.093636e-05 |
| 10,927 | MOMENTI: Scalable Motif Mining in Multidimensional Time Series | 2025 | VLDB | 5.093636e-05 |
| 11,249 | Efficient Discovery of Significant Patterns with Few-Shot Resampling | 2024 | VLDB | 5.093636e-05 |
Previous
Page 1 / 1
Next
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 |
|---|---|---|---|---|
| 810 | Similarity-Based Queries for Time Series Data | 1997 | SIGMOD | 0.00013874464 |
| 1,764 | Fast Approximate Correlation for Massive Time-series Data | 2010 | SIGMOD | 9.8120315e-05 |
| 2,541 | Locality-Sensitive Hashing for Earthquake Detection: A Case Study of Scaling Data-Driven Science | 2018 | VLDB | 8.4500033e-05 |
| 3,182 | VALMOD: A Suite for Easy and Exact Detection of Variable Length Motifs in Data Series | 2018 | SIGMOD | 7.6589981e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 8,542 | Online Windowed Subsequence Matching over Probabilistic Sequences | 2012 | SIGMOD |
| 2 | 6,784 | Motiflets - Simple and Accurate Detection of Motifs in Time Series | 2023 | VLDB |
| 3 | 3,252 | Fast Time-Series Searching with Scaling and Shifting | 1999 | PODS |
| 4 | 12,471 | Parsimonious Linear Fingerprinting for Time Series | 2010 | VLDB |
| 5 | 8,170 | Efficient Discovery of Sequence Outlier Patterns | 2019 | VLDB |
| 6 | 11,107 | Representative Time Series Discovery for Data Exploration | 2025 | VLDB |
| 7 | 10,859 | Time Series Motif Discovery: A Comprehensive Evaluation | 2025 | VLDB |
| 8 | 5,043 | Efficient Temporal Pattern Mining in Big Time Series Using Mutual Information | 2022 | VLDB |
| 9 | 5,325 | Rare Time Series Motif Discovery from Unbounded Streams | 2015 | VLDB |
| 10 | 10,927 | MOMENTI: Scalable Motif Mining in Multidimensional Time Series | 2025 | VLDB |