CDB: A Crowd-Powered Database System
Summary: CDB: crowd-powered DB with a graph-based, fine-grained tuple-level optimization model. Simultaneous cost, latency, and quality optimization; outperforms tree-based plans and enables real-world deployments for web table integration and entity collection. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Guoliang Li
- 2. Chengliang Chai
- 3. Ju Fan
- 4. Xueping Weng
- 5. Jian Li
- 6. Yudian Zheng
- 7. Yuanbing Li
- 8. Xiang Yu
- 9. Xiaohang Zhang
- 10. Haitao Yuan
Incoming Citations (Sorted by Pagerank)
Showing 10 of 10 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,839 | DocETL: Agentic Query Rewriting and Evaluation for Complex Document Processing | 2025 | VLDB | 0.00010351287 |
| 4,103 | GoodCore: Data-effective and Data-efficient Machine Learning through Coreset Selection over Incomplete Data | 2023 | SIGMOD | 6.4460899e-05 |
| 5,386 | Selective Data Acquisition in the Wild for Model Charging | 2022 | VLDB | 5.5346315e-05 |
| 5,744 | Efficient Algorithms for Crowd-Aided Categorization | 2020 | VLDB | 5.343155e-05 |
| 6,421 | Fluid: A Blockchain based Framework for Crowdsourcing | 2019 | SIGMOD | 5.0621949e-05 |
| 6,570 | Domain Adaptation for Deep Entity Resolution | 2022 | SIGMOD | 5.0017341e-05 |
| 7,580 | Human-in-the-loop Outlier Detection | 2020 | SIGMOD | 4.7023767e-05 |
| 9,043 | Query-Guided Resolution in Uncertain Databases | 2023 | SIGMOD | 4.3997447e-05 |
| 11,003 | MisDetect: Iterative Mislabel Detection using Early Loss | 2024 | VLDB | 4.1905499e-05 |
| 11,402 | ActivePDB: Active Probabilistic Databases | 2022 | VLDB | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 94 | CrowdDB: Answering Queries with Crowdsourcing | 2011 | SIGMOD | 0.00051273089 |
| 246 | Crowdsourced Databases: Query Processing with People | 2011 | CIDR | 0.00030952631 |
| 863 | Leveraging Transitive Relations for Crowdsourced Joins | 2013 | SIGMOD | 0.00015793243 |
| 2,944 | Truth Inference in Crowdsourcing: Is the Problem Solved? | 2017 | VLDB | 7.8457167e-05 |
| 3,268 | QASCA: A Quality-Aware Task Assignment System for Crowdsourcing Applications | 2015 | SIGMOD | 7.3027561e-05 |
| 4,580 | Crowdsourced Top-k Algorithms: An Experimental Evaluation | 2016 | VLDB | 6.0646299e-05 |
| 5,369 | Cost-Effective Crowdsourced Entity Resolution: A Partial-Order Approach | 2016 | SIGMOD | 5.5436995e-05 |
| 11,796 | CDB: Optimizing Queries with Crowd-Based Selections and Joins | 2017 | SIGMOD | 4.1905499e-05 |
| 11,824 | DOCS: Domain-Aware Crowdsourcing System | 2017 | VLDB | 4.1905499e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,801 | Query Optimization over Crowdsourced Data | 2013 | VLDB | 4.9175463e-05 |
| 510 | An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning | 2019 | SIGMOD | 0.00021420477 |
| 7,667 | Human-in-the-loop Data Integration | 2017 | VLDB | 4.6791871e-05 |
| 7,116 | Crowdsourced Data Management: Overview and Challenges | 2017 | SIGMOD | 4.8219732e-05 |
| 3,939 | CrowdQ: Crowdsourced Query Understanding | 2013 | CIDR | 6.6099823e-05 |
| 5,458 | Crowdsourcing Applications and Platforms: A Data Management Perspective | 2011 | VLDB | 5.4952003e-05 |
| 7,577 | Pushing the Boundaries of Crowd-enabled Databases with Query-driven Schema Expansion | 2012 | VLDB | 4.703047e-05 |
| 1,883 | CrowdDB: Query Processing with the VLDB Crowd | 2011 | VLDB | 0.00010208032 |
| 94 | CrowdDB: Answering Queries with Crowdsourcing | 2011 | SIGMOD | 0.00051273089 |
| 11,796 | CDB: Optimizing Queries with Crowd-Based Selections and Joins | 2017 | SIGMOD | 4.1905499e-05 |