TARImpute: Task-Aware auto-Recommender System for Missing Value Imputation Algorithms with Clustering Case Studies
Summary: TARImpute: a task-aware auto-recommender that selects imputation methods optimized for downstream clustering by profiling imputation–clustering interactions and modeling error propagation. Integrates impact profiling, error-propagation interpretation, and adaptive strategy optimization. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Xiaoou Ding
- 2. Yanshuo Liu
- 3. Zhounan Chen
- 4. Hongzhi Wang
- 5. Chen Wang
- 6. Jianmin Wang
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,276 | Mind the Gap: An Experimental Evaluation of Imputation of Missing Values Techniques in Time Series | 2020 | VLDB | 9.1261944e-05 |
| 3,825 | Cleanits: A Data Cleaning System for Industrial Time Series | 2019 | VLDB | 6.7255837e-05 |
| 9,558 | Clean4TSDB: A Data Cleaning Tool for Time Series Databases | 2024 | VLDB | 4.3254416e-05 |
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