MTSClean: Efficient Constraint-based Cleaning for Multi-Dimensional Time Series Data
Summary: MTSClean cleans multidimensional time series online by jointly exploiting row- and column-level constraints, capturing cross-attribute dependencies and persistent errors. Its exact and soft variants reduce computational complexity while improving repair precision over nine baselines. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Xiaoou Ding (Harbin Engineering University)
- 2. Yichen Song (Harbin Engineering University)
- 3. Hongzhi Wang (Harbin Engineering University)
- 4. Chen Wang (Tsinghua University)
- 5. Donghua Yang (Harbin Engineering University)
BibTeX Citation
@article{ding_vldb24,
title = {{MTSClean: Efficient Constraint-based Cleaning for Multi-Dimensional Time Series Data}},
author = {Ding, Xiaoou and Song, Yichen and Wang, Hongzhi and Wang, Chen and Yang, Donghua},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {13},
pages = {4840--4852},
doi = {10.14778/3704965.3704987},
url = {https://doi.org/10.14778/3704965.3704987},
year = {2024}
}Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,500 | SHoTClean: Bridging Soft and Hard Constraints for Multivariate Time Series Cleaning | 2026 | SIGMOD | 5.093636e-05 |
| 10,923 | Improving Time Series Data Compression in Apache IoTDB | 2025 | VLDB | 5.093636e-05 |
| 10,966 | UniClean: A Scalable Data Cleaning Solution for Mixed Errors based on Unified Cleaners and Optimized Cleaning Workflow | 2025 | VLDB | 5.093636e-05 |
| 11,038 | DemandClean: A Multi-Objective Learning Framework for Balancing Model Tolerance to Data Authenticity and Diversity | 2025 | VLDB | 5.093636e-05 |
| 11,079 | bNDCRepair: Cleaning both Data Errors and Inaccurate Constraints on Numerical Sequential Data | 2025 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 18 of 18 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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