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.

中文翻译：

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智能智能应用众包中的人群选择：系统映射研究

众包是一种任务解决模型，其中雇佣人群来解决特定任务。在众包过程中，进行众包选择，以便为特定任务选择合适的众包工作者；without appropriate selection of crowd workers, the process of crowdsourcing is aimless. 本文的主要目标是确定众包活动中人群的特征、人群参与众包活动的原因以及用于众包中人群选择的现有技术。使用具有相应关键字的搜索字符串来捕获与众包相关的研究，并将人群选择分类为会议论文、期刊文章、会议录和书籍章节。使用搜索策略从 7 个数字数据存储库中选择了 81 项相关研究。在众包实践中，众包选择得到了大量解决。尽管如此，已经注意到选择仅基于单一的众包工作者属性，例如信心、过去的成功、效率和经验。为了众包操作的效率和有效性，多标准特征的人群选择是必不可少的。