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 |
|---|---|---|---|---|
| 3,973 | HAIChart: Human and AI Paired Visualization System | 2024 | VLDB | 6.5721521e-05 |
| 4,103 | GoodCore: Data-effective and Data-efficient Machine Learning through Coreset Selection over Incomplete Data | 2023 | SIGMOD | 6.4460899e-05 |
| 4,829 | Synthesizing Natural Language to Visualization (NL2VIS) Benchmarks from NL2SQL Benchmarks | 2021 | SIGMOD | 5.8890126e-05 |
| 8,263 | Learned Data-aware Image Representations of Line Charts for Similarity Search | 2023 | SIGMOD | 4.5414364e-05 |
| 9,116 | Towards Observability for Production Machine Learning Pipelines | 2022 | VLDB | 4.3886184e-05 |
| 10,301 | LEAD: Iterative Data Selection for Efficient LLM Instruction Tuning | 2026 | VLDB | 4.1905499e-05 |
| 10,730 | UniClean: A Scalable Data Cleaning Solution for Mixed Errors based on Unified Cleaners and Optimized Cleaning Workflow | 2025 | VLDB | 4.1905499e-05 |
| 11,003 | MisDetect: Iterative Mislabel Detection using Early Loss | 2024 | VLDB | 4.1905499e-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 |
|---|---|---|---|---|
| 697 | Efficient Algorithms for Mining Outliers from Large Data Sets | 2000 | SIGMOD | 0.00017964755 |
| 705 | Magellan: Toward Building Entity Matching Management Systems | 2016 | VLDB | 0.00017779048 |
| 1,544 | KATARA: A Data Cleaning System Powered by Knowledge Bases and Crowdsourcing | 2015 | SIGMOD | 0.00011438274 |
| 2,805 | Query-Oriented Data Cleaning with Oracles | 2015 | SIGMOD | 8.103731e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,687 | IHCS: An Integrated Hybrid Cleaning System | 2019 | VLDB | 4.1905499e-05 |
| 1,629 | Data Cleaning: Overview and Emerging Challenges | 2016 | SIGMOD | 0.00011073148 |
| 6,383 | A Demonstration of DBWipes: Clean as You Query | 2012 | VLDB | 5.0831604e-05 |
| 198 | Declarative Data Cleaning: Language, Model, and Algorithms | 2001 | VLDB | 0.0003505869 |
| 7,233 | CleanM: An Optimizable Query Language for Unified Scale-Out Data Cleaning | 2017 | VLDB | 4.788267e-05 |
| 11,519 | From Papers to Practice: The openclean Open-Source Data Cleaning Library | 2021 | VLDB | 4.1905499e-05 |
| 788 | ActiveClean: Interactive Data Cleaning For Statistical Modeling | 2016 | VLDB | 0.00016618698 |
| 9,501 | Arachnid: Generalized Visual Data Cleaning | 2019 | SIGMOD | 4.3300131e-05 |
| 7,565 | PIClean: A Probabilistic and Interactive Data Cleaning System | 2019 | SIGMOD | 4.7048523e-05 |
| 5,930 | ActiveClean: An Interactive Data Cleaning Framework For Modern Machine Learning | 2016 | SIGMOD | 5.2632185e-05 |