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Modeling crowdsourcing systems: design and analysis of incentive mechanism and rating system

Published: 04 September 2014 Publication History
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References

[1]
Amazon Mechanical Turk. https://www.mturk.com.
[2]
R. Gibbons. Game theory for applied economists. Princeton University Press, 1992.
[3]
Helpouts. https://helpouts.google.com/home.
[4]
C.-J. Ho and J. W. Vaughan. Online task assignment in crowdsourcing markets. In Proc. of AAAI, 2012.
[5]
J. Howe. Crowdsourcing: Why the power of the crowd is driving the future of business. Crown Business, 2008.
[6]
E. I. Sparling and S. Sen. Rating: How difficult is it? In Proc. of ACM RecSys, 2011.
[7]
L. von Ahn, R. Liu, and M. Blum. Peekaboom: A game for locating objects in images. In Proc. of ACM CHI, 2006.
[8]
Yahoo! Answers. http://answers.yahoo.com.

Cited By

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  • (2023)Incentive Mechanism Design for Federated Learning and UnlearningProceedings of the Twenty-fourth International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing10.1145/3565287.3610269(11-20)Online publication date: 23-Oct-2023
  • (2023)Quality-Aware Incentive Mechanism for Mobile CrowdsourcingMobile Crowdsourcing10.1007/978-3-031-32397-3_4(91-116)Online publication date: 21-Apr-2023
  • (2021)Exploiting Multi-Dimensional Task Diversity in Distributed Auctions for Mobile CrowdsensingIEEE Transactions on Mobile Computing10.1109/TMC.2020.298788120:8(2576-2591)Online publication date: 1-Aug-2021
  • Show More Cited By

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Published In

cover image ACM SIGMETRICS Performance Evaluation Review
ACM SIGMETRICS Performance Evaluation Review  Volume 42, Issue 2
September 2014
74 pages
ISSN:0163-5999
DOI:10.1145/2667522
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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 September 2014
Published in SIGMETRICS Volume 42, Issue 2

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Cited By

View all
  • (2023)Incentive Mechanism Design for Federated Learning and UnlearningProceedings of the Twenty-fourth International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing10.1145/3565287.3610269(11-20)Online publication date: 23-Oct-2023
  • (2023)Quality-Aware Incentive Mechanism for Mobile CrowdsourcingMobile Crowdsourcing10.1007/978-3-031-32397-3_4(91-116)Online publication date: 21-Apr-2023
  • (2021)Exploiting Multi-Dimensional Task Diversity in Distributed Auctions for Mobile CrowdsensingIEEE Transactions on Mobile Computing10.1109/TMC.2020.298788120:8(2576-2591)Online publication date: 1-Aug-2021
  • (2020)FINESSE: Fair Incentives for Enterprise EmployeesResearch Challenges in Information Science10.1007/978-3-030-50316-1_12(191-211)Online publication date: 25-Jun-2020
  • (2017)Distributed Auctions for Task Assignment and Scheduling in Mobile Crowdsensing Systems2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)10.1109/ICDCS.2017.121(635-644)Online publication date: Jun-2017
  • (2015)Quality of Information Aware Incentive Mechanisms for Mobile Crowd Sensing SystemsProceedings of the 16th ACM International Symposium on Mobile Ad Hoc Networking and Computing10.1145/2746285.2746310(167-176)Online publication date: 22-Jun-2015
  • (2015)Improving Paid Microtasks through Gamification and Adaptive Furtherance IncentivesProceedings of the 24th International Conference on World Wide Web10.1145/2736277.2741639(333-343)Online publication date: 18-May-2015

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