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Selection of Crowd in Crowdsourcing for Smart Intelligent Applications: A Systematic Mapping Study

机译:智能智能应用中众包中的人群选择:系统映射研究

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Crowdsourcing is a task-solving model in which human crowd is hired to solve a particular task. During the crowdsourcing process, the crowd selection is performed in order to select appropriate crowd workers for a specific task; without appropriate selection of crowd workers, the process of crowdsourcing is aimless. The main goal of this paper was to identify the features of crowd in crowdsourcing activity, reasons behind crowd participation in the activity of crowdsourcing, and the existing techniques that were utilized for crowd selection in crowdsourcing. Search strings with corresponding keywords were used to capture relevant studies related to crowdsourcing, and crowd selection was classified under conference papers, journal articles, proceedings, and book chapters. 81 relevant studies are selected from 7 digital data repositories using a search strategy. In crowdsourcing practices, crowd selection was considerably addressed. Nonetheless, it has been noticed that the selection is based only on a single crowd worker attribute such as confidence, past success, efficiency, and experience. For the efficiency and effectiveness of the crowdsourcing operation, crowd selection on multicriteria features is essential.
机译:众包是一个任务解决模型,其中人们人群被雇用来解决特定任务。在众包流程期间,进行人群选择,以便为特定任务选择合适的人群工人; without appropriate selection of crowd workers, the process of crowdsourcing is aimless.本文的主要目的是识别人群中众群活动的特征,人群参与众包活动的原因,以及用于人群中众包中的现有技术。使用相应关键词的搜索字符串用于捕获与众包相关的相关研究,并且在会议论文,期刊文章,程序和书籍章节下归类为人群选择。 81相关研究选自使用搜索策略的7个数字数据存储库。在众包实践中,人群选择得到了大大解决。尽管如此,它已经注意到,该选择仅基于单一人群工人属性,如信心,过去的成功,效率和经验。对于众包运行的效率和有效性,人群选择对多标准功能至关重要。

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