TUCKET: A Tensor Time Series Data Structure for Efficient and Accurate Factor Analysis over Time Ranges
Summary: TUCKET introduces a stream segment tree for accurate, efficient Tucker decompositions over tensor time-range queries and streaming updates. It stitches O(log L) precomputed nodes, prunes them optimally, and updates only amortized O(1) nodes. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Ruizhong Qiu (University of Illinois Urbana-Champaign)
- 2. Jun-Gi Jang (University of Illinois Urbana-Champaign)
- 3. Xiao Lin (University of Illinois Urbana-Champaign)
- 4. Lihui Liu (University of Illinois Urbana-Champaign)
- 5. Hanghang Tong (University of Illinois Urbana-Champaign)
BibTeX Citation
@article{qiu_vldb24,
title = {{TUCKET: A Tensor Time Series Data Structure for Efficient and Accurate Factor Analysis over Time Ranges}},
author = {Qiu, Ruizhong and Jang, Jun-Gi and Lin, Xiao and Liu, Lihui and Tong, Hanghang},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {13},
pages = {4746--4759},
doi = {10.14778/3704965.3704980},
url = {https://doi.org/10.14778/3704965.3704980},
year = {2024}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,408 | SCOUT: Coupling-Free Bounds for Trillion-Scale Top-k Retrieval in Sparse Tensor Factorization | 2027 | SIGMOD | 4.9605343e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2 | R-Trees: A Dynamic Index Structure For Spatial Searching | 1984 | SIGMOD | 0.0019892478 |
| 3,351 | LittleTable: A Time-Series Database and Its Uses | 2017 | SIGMOD | 7.3729208e-05 |
| 3,634 | Apache IoTDB: A Time Series Database for IoT Applications | 2023 | SIGMOD | 7.1266347e-05 |
| 4,914 | triCluster: An Effective Algorithm for Mining Coherent Clusters in 3D Microarray Data | 2005 | SIGMOD | 6.3453058e-05 |
| 6,935 | LFTF: A Framework for Efficient Tensor Analytics at Scale | 2017 | VLDB | 5.6248915e-05 |
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