| 1,644 |
Apache IoTDB: Time-series Database for Internet of Things |
2020 |
VLDB |
23 |
9.9773086e-05 |
| 2,985 |
Time Series Data Cleaning: From Anomaly Detection to Anomaly Repairing |
2017 |
VLDB |
19 |
7.7695402e-05 |
| 3,634 |
Apache IoTDB: A Time Series Database for IoT Applications |
2023 |
SIGMOD |
26 |
7.1266347e-05 |
| 4,880 |
Time Series Data Encoding for Efficient Storage: A Comparative Analysis in Apache IoTDB |
2022 |
VLDB |
13 |
6.3566231e-05 |
| 5,131 |
Sequential Data Cleaning: A Statistical Approach |
2016 |
SIGMOD |
13 |
6.2464522e-05 |
| 5,296 |
Enriching Data Imputation with Extensive Similarity Neighbors |
2015 |
VLDB |
5 |
6.1777832e-05 |
| 6,322 |
SCREEN: Stream Data Cleaning under Speed Constraints |
2015 |
SIGMOD |
20 |
5.7959179e-05 |
| 7,554 |
Time Series Representation for Visualization in Apache IoTDB |
2024 |
SIGMOD |
3 |
5.4800579e-05 |
| 8,190 |
Efficient Recovery of Missing Events |
2013 |
VLDB |
2 |
5.3649295e-05 |
| 8,564 |
Why Not Match: On Explanations of Event Pattern Queries |
2021 |
SIGMOD |
2 |
5.2999122e-05 |
| 9,086 |
NLC: Search Correlated Window Pairs on Long Time Series |
2022 |
VLDB |
1 |
5.2094282e-05 |
| 9,094 |
DAFDiscover: Robust Mining Algorithm for Dynamic Approximate Functional Dependencies on Dirty Data |
2024 |
VLDB |
3 |
5.208561e-05 |
| 9,169 |
Distance-based Outlier Query Optimization in Apache IoTDB |
2024 |
VLDB |
2 |
5.2018272e-05 |
| 9,277 |
TsQuality: Measuring Time Series Data Quality in Apache IoTDB |
2023 |
VLDB |
1 |
5.1860131e-05 |
| 9,349 |
Apache TsFile: An IoT-native Time Series File Format |
2024 |
VLDB |
5 |
5.1763069e-05 |
| 9,603 |
Determining Exact Quantiles with Randomized Summaries |
2024 |
SIGMOD |
1 |
5.1376962e-05 |
| 9,733 |
Constraint-Variance Tolerant Data Repairing |
2016 |
SIGMOD |
3 |
5.1196037e-05 |
| 9,912 |
Clean4TSDB: A Data Cleaning Tool for Time Series Databases |
2024 |
VLDB |
7 |
5.0983269e-05 |
| 10,652 |
LSM-Raft: Optimizing Raft for LSM-tree Store |
2026 |
SIGMOD |
0 |
4.9605343e-05 |
| 11,179 |
Largest Triangle Sampling for Visualizing Time Series in Database |
2025 |
SIGMOD |
0 |
4.9605343e-05 |
| 11,310 |
Migration-Free Elastic Storage of Time Series in Apache IoTDB |
2025 |
VLDB |
0 |
4.9605343e-05 |
| 11,377 |
Improving Time Series Data Compression in Apache IoTDB |
2025 |
VLDB |
0 |
4.9605343e-05 |
| 11,462 |
TARImpute: Task-Aware auto-Recommender System for Missing Value Imputation Algorithms with Clustering Case Studies |
2025 |
VLDB |
1 |
4.9605343e-05 |
| 11,493 |
bNDCRepair: Cleaning both Data Errors and Inaccurate Constraints on Numerical Sequential Data |
2025 |
VLDB |
0 |
4.9605343e-05 |
| 11,640 |
On Reducing Space Amplification with Multi-Column Compaction in Apache IoTDB |
2024 |
VLDB |
0 |
4.9605343e-05 |
| 11,748 |
Grouping Time Series for Efficient Columnar Storage |
2023 |
SIGMOD |
4 |
4.9605343e-05 |
| 12,423 |
Cleaning Timestamps with Temporal Constraints |
2016 |
VLDB |
2 |
4.9605343e-05 |
| 12,492 |
Inferring Continuous Dynamic Social Influence and Personal Preference for Temporal Behavior Prediction |
2015 |
VLDB |
0 |
4.9605343e-05 |
| 12,507 |
Matching Heterogeneous Event Data |
2014 |
SIGMOD |
1 |
4.9605343e-05 |
| 14,064 |
MapDupReducer: Detecting Near Duplicates over Massive Datasets |
2010 |
SIGMOD |
2 |
- |