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A profile-aware microtasking approach for improving task assignment in crowdsourcing services

机译:一种配置文件感知型微任务处理方法,用于改善众包服务中的任务分配

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Microtasking as one of the crowdsourcing models has found penetration mostly in developed nations and is slowly making inroads in developing nations. It has been used for quickly solving a myriad of social and business challenges by tapping into the diversity of the unknown crowd. Nevertheless, there are still a number of research challenges that are found in various microtasking initiatives, such as lack of user profiling, quality of task submissions, poor task design and assignment, ambiguous task assessments, and lack of diverse platforms to cater for the needs of differently skilled crowds. Most prominent microtasking platforms do not consider or even exploit the profile of the crowd in improving task design, assignment, and eventually quality of completed microtasks. In this paper, the objective was to explore the design and evaluation of a conceptual approach that could be implemented in microtasking environments for purposes of improving task assignments and eventually quality. A design science research methodology was adopted to build the proposed artefact, which was evaluated for relevance using comparative analysis and crowdsourcing metrics. The results suggest that exploiting micro workers' profiles could improve task design, assignment, assessment, and ultimately quality. However, stakeholders' awareness of effective microtasking approaches still requires research attention.
机译:作为众包模式的一种,微任务已在发达国家普遍普及,并在发展中国家逐渐普及。通过利用未知人群的多样性,它已用于快速解决各种社会和商业挑战。尽管如此,在各种微任务处理计划中仍然存在许多研究挑战,例如缺乏用户概况分析,任务提交质量,任务设计和分配不佳,任务评估不明确以及缺乏满足需求的多样化平台不同技能的人群。大多数杰出的微任务平台在改善任务设计,分配以及最终完成的微任务的质量时,都没有考虑甚至利用人群的轮廓。在本文中,目标是探索可以在微任务环境中实施的概念方法的设计和评估,以改善任务分配并最终提高质量。采用了设计科学研究方法来构建拟议的人工制品,并使用比较分析和众包指标对其进行了相关性评估。结果表明,利用微型工人的个人资料可以改善任务设计,分配,评估和最终质量。但是,利益相关者对有效的微任务方法的认识仍然需要研究关注。

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