Efficient Discovery of Sequence Outlier Patterns
Summary: TOP introduces contextual outlier-pattern semantics that separate a pattern’s independent occurrences from those embedded in frequent super-patterns. Its top-down Reduce mining, context pruning, and inverted indexes achieve linear-time processing and up to 100× speedups on IoT sequences. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Lei Cao (Massachusetts Institute of Technology)
- 2. Yizhou Yan (Worcester Polytechnic Institute)
- 3. Samuel Madden (Massachusetts Institute of Technology)
- 4. Elke A. Rundensteiner (Worcester Polytechnic Institute)
- 5. Mathan Gopalsamy (Signify Research)
BibTeX Citation
@article{cao_vldb19,
title = {{Efficient Discovery of Sequence Outlier Patterns}},
author = {Cao, Lei and Yan, Yizhou and Madden, Samuel and Rundensteiner, Elke A. and Gopalsamy, Mathan},
journal = {PVLDB},
series = {{VLDB} '19},
volume = {12},
number = {8},
pages = {920--932},
doi = {10.14778/3324301.3324308},
url = {https://doi.org/10.14778/3324301.3324308},
year = {2019}
}Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,230 | TOD: GPU-accelerated Outlier Detection via Tensor Operations | 2023 | VLDB | 5.4619615e-05 |
| 11,249 | Efficient Discovery of Significant Patterns with Few-Shot Resampling | 2024 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 371 | Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases | 1995 | VLDB | 0.00019869565 |
| 4,942 | Active Complex Event Processing over Event Streams | 2011 | VLDB | 6.4333059e-05 |
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