AutoPlait: Automatic Mining of Co-evolving Time Sequences
Summary: AutoPlait automatically mines co-evolving time sequences with unknown pattern counts and diverse durations. Parameter-free, linear-scaling, no training or tuning, it detects similar segment groups and segments sequences; outperforms peers in precision/recall (>95%) and speed (up to 472x) on 67GB of real data. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,797 | Raising the ClaSS of Streaming Time Series Segmentation | 2024 | VLDB | 4.9241565e-05 |
| 9,147 | ISSD: Indicator Selection for Time Series State Detection | 2025 | SIGMOD | 4.3849295e-05 |
| 9,156 | Time2State: An Unsupervised Framework for Inferring the Latent States in Time Series Data | 2023 | SIGMOD | 4.3849295e-05 |
| 9,920 | Mining and Forecasting of Big Time-series Data | 2015 | SIGMOD | 4.2561557e-05 |
| 10,309 | CLaP - State Detection from Time Series | 2026 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 11 of 11 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 33 | BIRCH: An Efficient Data Clustering Method for Very Large Databases | 1996 | SIGMOD | 0.00077324389 |
| 358 | On The Marriage of Lp-norms and Edit Distance | 2004 | VLDB | 0.0002599481 |
| 1,045 | Adaptive Stream Resource Management Using Kalman Filters | 2004 | SIGMOD | 0.00014472777 |
| 1,126 | Trajectory Clustering: A Partition-and-Group Framework | 2007 | SIGMOD | 0.00013821443 |
| 1,346 | Streaming Pattern Discovery in Multiple Time-Series | 2005 | VLDB | 0.00012466288 |
| 2,680 | Finding Semantics in Time Series | 2011 | SIGMOD | 8.3234371e-05 |
| 2,889 | Prediction and Indexing of Moving Objects with Unknown Motion Patterns | 2004 | SIGMOD | 7.9587247e-05 |
| 3,519 | BRAID: Stream Mining through Group Lag Correlations | 2005 | SIGMOD | 7.0137199e-05 |
| 5,760 | Outlier-robust Clustering using Independent Components | 2008 | SIGMOD | 5.3382727e-05 |
| 5,808 | Leveraging Spatio-Temporal Redundancy for RFID Data Cleansing | 2010 | SIGMOD | 5.3185608e-05 |
| 12,276 | Parsimonious Linear Fingerprinting for Time Series | 2010 | VLDB | 4.1945683e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 13,113 | Fully Automated Correlated Time Series Forecasting in Minutes | 2025 | VLDB | - |
| 840 | Efficiently Mining Long Patterns from Databases | 1998 | SIGMOD | 0.00016058396 |
| 10,599 | Time Series Motif Discovery: A Comprehensive Evaluation | 2025 | VLDB | 4.1945683e-05 |
| 5,245 | Fast and Scalable Mining of Time Series Motifs with Probabilistic Guarantees | 2022 | VLDB | 5.6067361e-05 |
| 7,246 | Finding Relevant Patterns in Bursty Sequences | 2008 | VLDB | 4.790704e-05 |
| 3,184 | AutoAI-TS: AutoAI for Time Series Forecasting | 2021 | SIGMOD | 7.4198086e-05 |
| 4,947 | Efficient Temporal Pattern Mining in Big Time Series Using Mutual Information | 2022 | VLDB | 5.8123636e-05 |
| 9,920 | Mining and Forecasting of Big Time-series Data | 2015 | SIGMOD | 4.2561557e-05 |
| 10,678 | MOMENTI: Scalable Motif Mining in Multidimensional Time Series | 2025 | VLDB | 4.1945683e-05 |
| 12,276 | Parsimonious Linear Fingerprinting for Time Series | 2010 | VLDB | 4.1945683e-05 |