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Identifying and Rewarding Subcrowds in Crowdsourcing
Siyuan Liu, Xiuyi Fan, Chunyan Miao
1573 - 1574
10.3233/978-1-61499-672-9-1573
Frontiers in Artificial Intelligence and Applications
Volume 285: ECAI 2016
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.

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