Identifying and Rewarding Subcrowds in Crowdsourcing
Liu Siyuan, Fan Xiuyi, Miao Chunyan · Frontiers in artificial intelligence and applications · 2016
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.