众包中的任务分配研究

Danula Hettiachchi, V. Kostakos, Jorge Gonçalves
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引用次数: 20

摘要

质量改进方法对于收集高质量的众包数据至关重要,无论是用于研究还是工业应用。动态调整人群工作流参数的任务分配是一种流行且广泛适用的方法。在这项调查中,我们回顾了任务分配方法,这些方法解决了众包中的异构任务分配、问题分配和多元性问题。我们讨论并对比了这些方法如何评估员工绩效,并强调了其实施中的潜在挑战。最后,我们讨论了任务分配方法的未来研究方向,以及众包平台和其他利益相关者如何从中受益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Survey on Task Assignment in Crowdsourcing
Quality improvement methods are essential to gathering high-quality crowdsourced data, both for research and industry applications. A popular and broadly applicable method is task assignment that dynamically adjusts crowd workflow parameters. In this survey, we review task assignment methods that address: heterogeneous task assignment, question assignment, and plurality problems in crowdsourcing. We discuss and contrast how these methods estimate worker performance, and highlight potential challenges in their implementation. Finally, we discuss future research directions for task assignment methods, and how crowdsourcing platforms and other stakeholders can benefit from them.
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