Argonaut: Macrotask Crowdsourcing for Complex Data Processing
Summary: Argonaut automates macrotask crowdsourcing for complex data tasks, with hierarchical reviews and predictive quality models to optimize depth. Deployment in a large structured-data pipeline shows up to 118% more errors detected than random spot-checks. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Daniel Haas (University of California Berkeley)
- 2. Jason Ansel (GoDaddy)
- 3. Lydia Gu (GoDaddy)
- 4. Adam Marcus (Unlimited Labs)
BibTeX Citation
@article{haas_vldb15,
title = {{Argonaut: Macrotask Crowdsourcing for Complex Data Processing}},
author = {Haas, Daniel and Ansel, Jason and Gu, Lydia and Marcus, Adam},
journal = {PVLDB},
series = {{VLDB} '15},
volume = {8},
number = {12},
pages = {1642--1653},
doi = {10.14778/2824032.2824062},
url = {https://doi.org/10.14778/2824032.2824062},
year = {2015}
}Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,791 | Crowdsourced Data Management: Overview and Challenges | 2017 | SIGMOD | 5.6647309e-05 |
| 12,231 | The Ever Evolving Online Labor Market: Overview, Challenges and Opportunities | 2019 | VLDB | 4.9605343e-05 |
| 12,410 | Collaborative Crowdsourcing with Crowd4U | 2016 | VLDB | 4.9605343e-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 |
|---|---|---|---|---|
| 92 | CrowdDB: Answering Queries with Crowdsourcing | 2011 | SIGMOD | 0.00034613457 |
| 199 | CrowdER: Crowdsourcing Entity Resolution | 2012 | VLDB | 0.0002551523 |
| 266 | Human-powered Sorts and Joins | 2012 | VLDB | 0.00022701006 |
| 434 | Corleone: Hands-Off Crowdsourcing for Entity Matching | 2014 | SIGMOD | 0.00018323777 |
| 516 | Data Curation at Scale: The Data Tamer System | 2013 | CIDR | 0.00016963937 |
| 535 | On Active Learning of Record Matching Packages | 2010 | SIGMOD | 0.00016768308 |
| 600 | Extracting Structured Data from Web Pages | 2003 | SIGMOD | 0.00015700403 |
| 932 | Question Selection for Crowd Entity Resolution | 2013 | VLDB | 0.00012981731 |
| 2,650 | CrowdFill: Collecting Structured Data from the Crowd | 2014 | SIGMOD | 8.1519618e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 10,081 | CrowdDQS: Dynamic Question Selection in Crowdsourcing Systems | 2017 | SIGMOD |
| 2 | 7,074 | Cost-Effective Data Annotation using Game-Based Crowdsourcing | 2019 | VLDB |
| 3 | 266 | Human-powered Sorts and Joins | 2012 | VLDB |
| 4 | 5,627 | CrowdQ: Crowdsourced Query Understanding | 2013 | CIDR |
| 5 | 4,537 | Arnold: Declarative Crowd-Machine Data Integration | 2013 | CIDR |
| 6 | 4,673 | CrowdMatcher: Crowd-Assisted Schema Matching | 2014 | SIGMOD |
| 7 | 92 | CrowdDB: Answering Queries with Crowdsourcing | 2011 | SIGMOD |
| 8 | 12,410 | Collaborative Crowdsourcing with Crowd4U | 2016 | VLDB |
| 9 | 257 | Crowdsourced Databases: Query Processing with People | 2011 | CIDR |
| 10 | 3,210 | iCrowd: An Adaptive Crowdsourcing Framework | 2015 | SIGMOD |