ORBITS: Online Recovery of Missing Values in Multiple Time Series Streams
Summary: ORBITS recovers missing blocks in multiple time series online via incremental centroid decomposition, yielding linear-time imputation. Correctness proof and real-world evaluation show ~30% more accuracy over state-of-the-art with much higher efficiency. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Mourad Khayati (University of Freiburg)
- 2. Ines Arous (University of Freiburg)
- 3. Zakhar Tymchenko (University of Freiburg)
- 4. Philippe Cudré-Mauroux (University of Freiburg)
BibTeX Citation
@article{khayati_vldb21,
title = {{ORBITS: Online Recovery of Missing Values in Multiple Time Series Streams}},
author = {Khayati, Mourad and Arous, Ines and Tymchenko, Zakhar and Cudré-Mauroux, Philippe},
journal = {PVLDB},
series = {{VLDB} '21},
volume = {14},
number = {3},
pages = {294--306},
doi = {10.14778/3430915.3430920},
url = {https://doi.org/10.14778/3430915.3430920},
year = {2021}
}Incoming Citations (Sorted by Pagerank)
Showing 8 of 8 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,844 | Missing Value Imputation for Multi-attribute Sensor Data Streams via Message Propagation | 2024 | VLDB | 5.5332653e-05 |
| 8,959 | TSM-Bench: Benchmarking Time Series Database Systems for Monitoring Applications | 2023 | VLDB | 5.3444909e-05 |
| 9,285 | ZIP: Lazy Imputation during Query Processing | 2024 | VLDB | 5.292293e-05 |
| 9,390 | ImputeVIS: An Interactive Evaluator to Benchmark Imputation Techniques for Time Series Data | 2024 | VLDB | 5.2755515e-05 |
| 9,993 | In-Database Data Imputation | 2024 | SIGMOD | 5.1815618e-05 |
| 10,981 | DIM-SUM: Dynamic Imputation for Smart Utility Management | 2025 | VLDB | 5.093636e-05 |
| 11,262 | Enriching Relations with Additional Attributes for ER | 2024 | VLDB | 5.093636e-05 |
| 11,424 | Splitting Tuples of Mismatched Entities | 2023 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,252 | Streaming Pattern Discovery in Multiple Time-Series | 2005 | VLDB | 0.00011483752 |
| 1,557 | Distance-based Outlier Detection in Data Streams | 2016 | VLDB | 0.00010367451 |
| 2,059 | LINVIEW: Incremental View Maintenance for Complex Analytical Queries | 2014 | SIGMOD | 9.2471145e-05 |
| 2,123 | Discovery of Genuine Functional Dependencies from Relational Data with Missing Values | 2018 | VLDB | 9.1372798e-05 |
| 2,208 | Query Optimization for Dynamic Imputation | 2017 | VLDB | 8.9512455e-05 |
| 2,545 | Mind the Gap: An Experimental Evaluation of Imputation of Missing Values Techniques in Time Series | 2020 | VLDB | 8.4401333e-05 |
| 2,995 | Time Series Data Cleaning: From Anomaly Detection to Anomaly Repairing | 2017 | VLDB | 7.8750141e-05 |
| 3,425 | Foresight: Recommending Visual Insights | 2017 | VLDB | 7.42218e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 8,008 | Efficient Recovery of Missing Events | 2013 | VLDB |
| 2 | 2,441 | Optimal Multi-scale Patterns in Time Series Streams | 2006 | SIGMOD |
| 3 | 10,784 | The Best of Both Worlds: On Repairing Timestamps and Attribute Values for Multivariate Time Series | 2025 | SIGMOD |
| 4 | 5,946 | Streaming Anomaly Detection Using Randomized Matrix Sketching | 2016 | VLDB |
| 5 | 9,390 | ImputeVIS: An Interactive Evaluator to Benchmark Imputation Techniques for Time Series Data | 2024 | VLDB |
| 6 | 2,171 | Multi-Dimensional Regression Analysis of Time-Series Data Streams | 2002 | VLDB |
| 7 | 2,995 | Time Series Data Cleaning: From Anomaly Detection to Anomaly Repairing | 2017 | VLDB |
| 8 | 9,199 | On Repairing Timestamps for Regular Interval Time Series | 2022 | VLDB |
| 9 | 7,844 | Missing Value Imputation for Multi-attribute Sensor Data Streams via Message Propagation | 2024 | VLDB |
| 10 | 2,545 | Mind the Gap: An Experimental Evaluation of Imputation of Missing Values Techniques in Time Series | 2020 | VLDB |