Efficient Temporal Pattern Mining in Big Time Series Using Mutual Information
Summary: Introduces FTPMfTS, a pipeline for mining temporal patterns from time series with event-time intervals. HTPGM enables fast pruning-based mining; an MI-based variant prunes unpromising series, delivering speedups with bounded accuracy. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Van Long Ho (Aalborg University)
- 2. Nguyen Ho (Aalborg University)
- 3. Torben Bach Pedersen (Aalborg University)
BibTeX Citation
@article{ho_vldb22,
title = {{Efficient Temporal Pattern Mining in Big Time Series Using Mutual Information}},
author = {Ho, Van Long and Ho, Nguyen and Pedersen, Torben Bach},
journal = {PVLDB},
series = {{VLDB} '22},
volume = {15},
number = {3},
pages = {673--685},
doi = {10.14778/3494124.3494147},
url = {https://doi.org/10.14778/3494124.3494147},
year = {2022}
}Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,498 | SimpleTS: An Efficient and Universal Model Selection Framework for Time Series Forecasting | 2023 | VLDB | 6.1972571e-05 |
| 7,104 | Akane: Perplexity-Guided Time Series Data Cleaning | 2024 | SIGMOD | 5.7020425e-05 |
| 11,249 | Efficient Discovery of Significant Patterns with Few-Shot Resampling | 2024 | VLDB | 5.093636e-05 |
| 11,402 | LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation | 2023 | SIGMOD | 5.093636e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 1 of 1 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,842 | Mining Relationships Among Interval-based Events for Classification | 2008 | SIGMOD | 6.4828227e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 14,090 | Towards Data Mining Benchmarking: A Test Bed for Performance Study of Frequent Pattern Mining | 2000 | SIGMOD |
| 2 | 3,920 | Continually Evaluating Similarity-Based Pattern Queries on a Streaming Time Series | 2002 | SIGMOD |
| 3 | 4,842 | Mining Relationships Among Interval-based Events for Classification | 2008 | SIGMOD |
| 4 | 10,859 | Time Series Motif Discovery: A Comprehensive Evaluation | 2025 | VLDB |
| 5 | 10,069 | Mining and Forecasting of Big Time-series Data | 2015 | SIGMOD |
| 6 | 8,170 | Efficient Discovery of Sequence Outlier Patterns | 2019 | VLDB |
| 7 | 161 | Mining Frequent Patterns without Candidate Generation | 2000 | SIGMOD |
| 8 | 10,927 | MOMENTI: Scalable Motif Mining in Multidimensional Time Series | 2025 | VLDB |
| 9 | 5,266 | Fast and Scalable Mining of Time Series Motifs with Probabilistic Guarantees | 2022 | VLDB |
| 10 | 6,305 | A Regression-Based Temporal Pattern Mining Scheme for Data Streams | 2003 | VLDB |