Back to papers
QASCA: A Quality-Aware Task Assignment System for Crowdsourcing Applications
Summary: QASCA is a quality-aware online task assignment system for crowdsourcing on AMT. It models probabilistic ground truths from worker answers to optimize Accuracy and F-score, delivering linear-time assignment and achieving about 8% quality gains across five real applications.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 5047
- Venue
- SIGMOD
- Year
- 2015
- Pagerank
- 7.3097573e-05
- Overall Rank
- 3,263 | 77.31%
- DOI
-
10.1145/2723372.2749430
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 16 of 16 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 2,937 |
Truth Inference in Crowdsourcing: Is the Problem Solved? |
2017 |
VLDB |
7.853108e-05 |
| 3,773 |
Cleaning Crowdsourced Labels Using Oracles for Statistical Classification |
2019 |
VLDB |
6.7758649e-05 |
| 5,279 |
CDB: A Crowd-Powered Database System |
2018 |
VLDB |
5.5902418e-05 |
| 5,362 |
Cost-Effective Crowdsourced Entity Resolution: A Partial-Order Approach |
2016 |
SIGMOD |
5.5473503e-05 |
| 5,734 |
Efficient Algorithms for Crowd-Aided Categorization |
2020 |
VLDB |
5.3482904e-05 |
| 6,868 |
Cost-Effective Data Annotation using Game-Based Crowdsourcing |
2019 |
VLDB |
4.9010083e-05 |
| 7,117 |
Crowdsourced Data Management: Overview and Challenges |
2017 |
SIGMOD |
4.826509e-05 |
| 7,292 |
Subjective Knowledge Base Construction Powered By Crowdsourcing and Knowledge Base |
2018 |
SIGMOD |
4.7740174e-05 |
| 7,575 |
Human-in-the-loop Outlier Detection |
2020 |
SIGMOD |
4.7068909e-05 |
| 7,668 |
Human-in-the-loop Data Integration |
2017 |
VLDB |
4.6834075e-05 |
| 11,611 |
CONCIERGE: Improving Constrained Search Results by Data Melioration |
2020 |
VLDB |
4.1945683e-05 |
| 11,707 |
A Rating-Ranking Method for Crowdsourced Top-k Computation |
2018 |
SIGMOD |
4.1945683e-05 |
| 11,750 |
Worker Recommendation for Crowdsourced Q&A Services: A Triple-Factor Aware Approach |
2018 |
VLDB |
4.1945683e-05 |
| 11,788 |
CDB: Optimizing Queries with Crowd-Based Selections and Joins |
2017 |
SIGMOD |
4.1945683e-05 |
| 11,791 |
CrowdDQS: Dynamic Question Selection in Crowdsourcing Systems |
2017 |
SIGMOD |
4.1945683e-05 |
| 11,816 |
DOCS: Domain-Aware Crowdsourcing System |
2017 |
VLDB |
4.1945683e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 21 of 21 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 |
0.00051013264 |
| 249 |
Crowdsourced Databases: Query Processing with People |
2011 |
CIDR |
0.00030740523 |
| 263 |
CrowdER: Crowdsourcing Entity Resolution |
2012 |
VLDB |
0.00029862413 |
| 267 |
Human-powered Sorts and Joins |
2012 |
VLDB |
0.00029690405 |
| 371 |
A Bayesian Approach to Discovering Truth from Conflicting Sources for Data Integration |
2012 |
VLDB |
0.00025389696 |
| 447 |
Efficient Parallel Set-Similarity Joins Using MapReduce |
2010 |
SIGMOD |
0.00022900171 |
| 692 |
Pay-as-you-go User Feedback for Dataspace Systems |
2008 |
SIGMOD |
0.00018083948 |
| 859 |
So Who Won? Dynamic Max Discovery with the Crowd |
2012 |
SIGMOD |
0.00015870894 |
| 866 |
Leveraging Transitive Relations for Crowdsourced Joins |
2013 |
SIGMOD |
0.00015801196 |
| 908 |
Fusing Data with Correlations |
2014 |
SIGMOD |
0.00015431241 |
| 1,164 |
CrowdScreen: Algorithms for Filtering Data with Humans |
2012 |
SIGMOD |
0.00013564823 |
| 1,211 |
Truth Finding on the Deep Web: Is the Problem Solved? |
2013 |
VLDB |
0.00013257101 |
| 1,242 |
Question Selection for Crowd Entity Resolution |
2013 |
VLDB |
0.00013096655 |
| 1,396 |
Can We Beat the Prefix Filtering? An Adaptive Framework for Similarity Join and Search |
2012 |
SIGMOD |
0.00012204748 |
| 1,491 |
CDAS: A Crowdsourcing Data Analytics System |
2012 |
VLDB |
0.00011694982 |
| 2,184 |
A Sample-and-Clean Framework for Fast and Accurate Query Processing on Dirty Data |
2014 |
SIGMOD |
9.3429789e-05 |
| 2,334 |
Counting with the Crowd |
2013 |
VLDB |
9.0161817e-05 |
| 2,809 |
Deco: A System for Declarative Crowdsourcing |
2012 |
VLDB |
8.0869896e-05 |
| 3,177 |
Evaluating Entity Resolution Results |
2010 |
VLDB |
7.4367331e-05 |
| 4,827 |
An Online Cost Sensitive Decision-Making Method in Crowdsourcing Systems |
2013 |
SIGMOD |
5.8938399e-05 |
| 5,081 |
Reducing Uncertainty of Schema Matching via Crowdsourcing |
2013 |
VLDB |
5.7132042e-05 |
Semantically Similar Papers
| Overall Rank |
Paper |
Year |
Venue |
Pagerank |
| 3,118 |
Scaling Up Crowd-Sourcing to Very Large Datasets: A Case for Active Learning |
2015 |
VLDB |
7.5379338e-05 |
| 8,063 |
An Experimental Evaluation of Task Assignment in Spatial Crowdsourcing |
2018 |
VLDB |
4.594024e-05 |
| 8,362 |
Minimizing Efforts in Validating Crowd Answers |
2015 |
SIGMOD |
4.5366717e-05 |
| 1,242 |
Question Selection for Crowd Entity Resolution |
2013 |
VLDB |
0.00013096655 |
| 11,750 |
Worker Recommendation for Crowdsourced Q&A Services: A Triple-Factor Aware Approach |
2018 |
VLDB |
4.1945683e-05 |
| 7,178 |
Towards Globally Optimal Crowdsourcing Quality Management: The Uniform Worker Setting |
2016 |
SIGMOD |
4.8085946e-05 |
| 4,827 |
An Online Cost Sensitive Decision-Making Method in Crowdsourcing Systems |
2013 |
SIGMOD |
5.8938399e-05 |
| 1,491 |
CDAS: A Crowdsourcing Data Analytics System |
2012 |
VLDB |
0.00011694982 |
| 3,322 |
iCrowd: An Adaptive Crowdsourcing Framework |
2015 |
SIGMOD |
7.2230626e-05 |
| 11,791 |
CrowdDQS: Dynamic Question Selection in Crowdsourcing Systems |
2017 |
SIGMOD |
4.1945683e-05 |