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Identifying and Rewarding Subcrowds in Crowdsourcing


Authors: S. Liu, X. Fan, and C. Miao
Title: Identifying and Rewarding Subcrowds in Crowdsourcing
Abstract: Identifying and rewarding truthful workers are key to the sustainability of crowdsourcing platforms. In this paper, we present a clustering based rewarding mechanism that rewards workers based on their truthfulness while accommodating the differences in workers’ preferences. Experimental results show that the proposed approach can effectively discover subcrowds under various conditions, and truthful workers are better rewarded than less truthful ones.
Keywords: 
Conference Name: 22nd European Conference on Artificial Intelligence (ECAI'16)
Location: The Hague, Holland
Publisher: IOS Press
Year: 2016
Accepted PDF File: Identifying_and_Rewarding_Subcrowds_in_Crowdsourcing_accepted.pdf
Permanent Link: http://dx.doi.org/10.3233/978-1-61499-672-9-1573
Reference: S. Liu, X. Fan, and C. Miao, “Identifying and rewarding subcrowds in crowdsourcing,” in Proceedings of the 22nd European Conference on Artificial Intelligence (ECAI’16). IOS Press, August–September 2016, pp. 1573–1574.
bibtex: 
@inproceedings{LILY-c99, 
    author	= {Liu, Siyuan and Fan, Xiuyi and Miao, Chunyan},
    title	= {Identifying and Rewarding Subcrowds in Crowdsourcing},  
    booktitle	= {Proceedings of the 22nd European Conference on Artificial Intelligence (ECAI'16)}, 
    year		= {2016}, 
    month	= {August--September}, 
    pages	= {1573-1574}, 
    location	= {The Hague, Holland},
    publisher	= {IOS Press},
 }