On Repairing Timestamps for Regular Interval Time Series
Summary: Formalizes timestamp repair problem for regular-interval time series; proposes exact pruning-based methods and a bi-directional DP approximation. Demonstrates higher repair accuracy, enables data-quality measures, and is implemented in Apache IoTDB. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Chenguang Fang
- 2. Shaoxu Song
- 3. Yinan Mei
Incoming Citations (Sorted by Pagerank)
Showing 9 of 9 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,971 | Apache IoTDB: A Time Series Database for IoT Applications | 2023 | SIGMOD | 6.5733348e-05 |
| 6,859 | Frequency Domain Data Encoding in Apache IoTDB | 2023 | VLDB | 4.9011567e-05 |
| 8,426 | Time Series Representation for Visualization in Apache IoTDB | 2024 | SIGMOD | 4.5098472e-05 |
| 8,914 | TsQuality: Measuring Time Series Data Quality in Apache IoTDB | 2023 | VLDB | 4.4229886e-05 |
| 9,127 | Apache TsFile: An IoT-native Time Series File Format | 2024 | VLDB | 4.3867836e-05 |
| 9,795 | Optimizing Time Series Queries with Versions | 2024 | SIGMOD | 4.2777144e-05 |
| 10,391 | In-Database Time Series Clustering | 2025 | SIGMOD | 4.1905499e-05 |
| 10,520 | The Best of Both Worlds: On Repairing Timestamps and Attribute Values for Multivariate Time Series | 2025 | SIGMOD | 4.1905499e-05 |
| 10,596 | SimRN: Trajectory Similarity Learning in Road Networks based on Distributed Deep Reinforcement Learning | 2025 | VLDB | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 251 | Robust and Fast Similarity Search for Moving Object Trajectories | 2005 | SIGMOD | 0.00030589775 |
| 268 | A Cost-Based Model and Effective Heuristic for Repairing Constraints by Value Modification | 2005 | SIGMOD | 0.00029739054 |
| 556 | Discovering Denial Constraints | 2013 | VLDB | 0.00020214701 |
| 1,925 | Apache IoTDB: Time-series Database for Internet of Things | 2020 | VLDB | 0.00010073156 |
| 5,851 | Mining Significant Semantic Locations From GPS Data | 2010 | VLDB | 5.3005017e-05 |
| 6,582 | SCREEN: Stream Data Cleaning under Speed Constraints | 2015 | SIGMOD | 4.9979977e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,558 | Clean4TSDB: A Data Cleaning Tool for Time Series Databases | 2024 | VLDB | 4.3212967e-05 |
| 10,140 | Analyzing Deviations from Monotonic Trends through Database Repair | 2026 | SIGMOD | 4.1905499e-05 |
| 11,178 | Grouping Time Series for Efficient Columnar Storage | 2023 | SIGMOD | 4.1905499e-05 |
| 10,391 | In-Database Time Series Clustering | 2025 | SIGMOD | 4.1905499e-05 |
| 10,061 | Cleaning Time Series under Seasonal and Trend Constraints | 2026 | SIGMOD | 4.1905499e-05 |
| 7,390 | Time Series Data Validity | 2023 | SIGMOD | 4.7383798e-05 |
| 3,142 | Time Series Data Cleaning: From Anomaly Detection to Anomaly Repairing | 2017 | VLDB | 7.4905759e-05 |
| 10,081 | From Suspicious Errors to Valid Data: On Repairing Spatio-Temporal Data via Spatial and Temporal Dependencies | 2026 | SIGMOD | 4.1905499e-05 |
| 10,520 | The Best of Both Worlds: On Repairing Timestamps and Attribute Values for Multivariate Time Series | 2025 | SIGMOD | 4.1905499e-05 |
| 11,889 | Cleaning Timestamps with Temporal Constraints | 2016 | VLDB | 4.1905499e-05 |