VisClean: Interactive Cleaning for Progressive Visualization
Summary: VisClean enables progressive, visualization-aware data cleaning to improve visualizations derived from dirty data. It provides an interactive GUI that lets users answer cleaning questions easily, yielding substantial visualization quality gains with only a few interactions. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yuyu Luo
- 2. Chengliang Chai
- 3. Xuedi Qin
- 4. Nan Tang
- 5. Guoliang Li
Incoming Citations (Sorted by Pagerank)
Showing 8 of 8 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,970 | HAIChart: Human and AI Paired Visualization System | 2024 | VLDB | 6.5784767e-05 |
| 4,102 | GoodCore: Data-effective and Data-efficient Machine Learning through Coreset Selection over Incomplete Data | 2023 | SIGMOD | 6.4522929e-05 |
| 4,825 | Synthesizing Natural Language to Visualization (NL2VIS) Benchmarks from NL2SQL Benchmarks | 2021 | SIGMOD | 5.8946721e-05 |
| 8,268 | Learned Data-aware Image Representations of Line Charts for Similarity Search | 2023 | SIGMOD | 4.5456668e-05 |
| 9,118 | Towards Observability for Production Machine Learning Pipelines | 2022 | VLDB | 4.3928288e-05 |
| 10,289 | LEAD: Iterative Data Selection for Efficient LLM Instruction Tuning | 2026 | VLDB | 4.1945683e-05 |
| 10,723 | UniClean: A Scalable Data Cleaning Solution for Mixed Errors based on Unified Cleaners and Optimized Cleaning Workflow | 2025 | VLDB | 4.1945683e-05 |
| 11,000 | MisDetect: Iterative Mislabel Detection using Early Loss | 2024 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 701 | Efficient Algorithms for Mining Outliers from Large Data Sets | 2000 | SIGMOD | 0.00017938417 |
| 712 | Magellan: Toward Building Entity Matching Management Systems | 2016 | VLDB | 0.00017732426 |
| 1,546 | KATARA: A Data Cleaning System Powered by Knowledge Bases and Crowdsourcing | 2015 | SIGMOD | 0.00011446851 |
| 2,797 | Query-Oriented Data Cleaning with Oracles | 2015 | SIGMOD | 8.1108589e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,682 | IHCS: An Integrated Hybrid Cleaning System | 2019 | VLDB | 4.1945683e-05 |
| 1,627 | Data Cleaning: Overview and Emerging Challenges | 2016 | SIGMOD | 0.00011086905 |
| 6,384 | A Demonstration of DBWipes: Clean as You Query | 2012 | VLDB | 5.0880333e-05 |
| 199 | Declarative Data Cleaning: Language, Model, and Algorithms | 2001 | VLDB | 0.00035041015 |
| 7,237 | CleanM: An Optimizable Query Language for Unified Scale-Out Data Cleaning | 2017 | VLDB | 4.7928651e-05 |
| 11,515 | From Papers to Practice: The openclean Open-Source Data Cleaning Library | 2021 | VLDB | 4.1945683e-05 |
| 791 | ActiveClean: Interactive Data Cleaning For Statistical Modeling | 2016 | VLDB | 0.00016629664 |
| 9,500 | Arachnid: Generalized Visual Data Cleaning | 2019 | SIGMOD | 4.3341665e-05 |
| 7,564 | PIClean: A Probabilistic and Interactive Data Cleaning System | 2019 | SIGMOD | 4.7093702e-05 |
| 5,929 | ActiveClean: An Interactive Data Cleaning Framework For Modern Machine Learning | 2016 | SIGMOD | 5.2682177e-05 |