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A visual analysis approach to validate the selection review of primary studies in systematic reviews

机译:一种视觉分析方法,可在系统评价中验证对主要研究的选择评价

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摘要

Context: Systematic Literature Reviews (SLRs) are an important component to identify and aggregate research evidence from different empirical studies. Despite its relevance, most of the process is conducted manually, implying additional effort when the Selection Review task is performed and leading to reading all studies under analysis more than once. Objective: We propose an approach based on Visual Text Mining (VTM) techniques to assist the Selection Review task in SLR. It is implemented into a VTM tool (Revis), which is freely available for use. Method: We have selected and implemented appropriate visualization techniques into our approach and validated and demonstrated its usefulness in performing real SLRs. Results: The results have shown that employment of VTM techniques can successfully assist in the Selection Review task, speeding up the entire SLR process in comparison to the conventional approach. Conclusions: VTM techniques are valuable tools to be used in the context of selecting studies in the SLR process, prone to speed up some stages of SLRs.
机译:背景:系统文献综述(SLR)是识别和汇总来自不同实证研究的研究证据的重要组成部分。尽管有相关性,但大多数过程都是手动执行的,这意味着在执行“选择审查”任务时会付出额外的努力,并导致不止一次地读取所有正在分析的研究。目的:我们提出一种基于视觉文本挖掘(VTM)技术的方法来协助SLR中的“选择审查”任务。它已在VTM工具(Revis)中实现,可以免费使用。方法:我们已经选择了合适的可视化技术并将其实施到我们的方法中,并验证并证明了其在执行实际SLR方面的有用性。结果:结果表明,与传统方法相比,使用VTM技术可以成功地协助“选择审查”任务,从而加快整个SLR过程。结论:VTM技术是在SLR过程中选择研究时使用的有价值的工具,易于加快SLR的某些阶段。

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