Context: In order to preserve the value of Systematic Reviews (SRs), they should be frequently updated considering new evidence that has been produced since the completion of the previous version of the reviews. However, the update of an SR is a time consuming, manual task. Thus, many SRs have not been updated as they should be and, therefore, they are currently outdated. Objective: The main contribution of this paper is to support the update of SRs. Method: We propose USR-VTM, an approach based on Visual Text Mining (VTM) techniques, to support selection of new evidence in the form of primary studies. We then present a tool, named Revis, which supports our approach. Finally, we evaluate our approach through a comparison of outcomes achieved using USR-VTM versus the traditional (manual) approach. Results: Our results show that USR-VTM increases the number of studies correctly included compared to the traditional approach. Conclusions: USR-VTM effectively supports the update of SRs.
翻译：目标:为了保持系统审查的价值,应经常更新这些审查,以考虑到自完成前一次审查以来产生的新证据。然而,更新SR是一项耗费时间的手工工作。因此,许多SR没有按其应有的方式更新,因此,它们目前已经过时。目标:本文件的主要贡献是支持更新SR。方法:我们建议USR-VTM, 一种基于视觉文本采矿技术的方法, 支持以初级研究形式选择新证据。然后,我们提出了一个工具,名为Revis, 支持我们的方法。最后,我们通过比较使用USR-VTM取得的结果与传统的(手工)方法相比较,评估我们的方法。结果:我们的结果表明,USR-VTM增加了与传统方法相比正确列入的研究报告的数量。结论:USR-VTM有效地支持了SR的更新。
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