Systematic reviews are comprehensive literature reviews that target a highly focused research question. In the medical domain, complex Boolean queries are used to identify studies. To ensure comprehensiveness, all studies retrieved are screened for inclusion or exclusion in the review. Developing Boolean queries for this task requires the expertise of trained information specialists. However, even for these expert searchers, query formulation can be difficult and lengthy: especially when dealing with areas of medicine that they may not be knowledgeable about. To this end, two computational adaptations of methods information specialists use to formulate Boolean queries have been proposed in prior work. These adaptations can be used to assist information specialists by providing a good starting point for query development. However, a number of limitations with these computational methods have been raised, and a comparison between them has not been made. In this study, we address the limitations of previous work and evaluate the two. We found that, between the two computational adaptions, the objective method is more effective than the conceptual method for query formulation alone, however, the conceptual method provides a better starting point for manual query refinement. This work helps to inform those building search tools that assist with systematic review construction.

系统评价是针对高度关注的研究问题的综合文献综述。在医学领域，复杂的布尔查询用于识别研究。为确保全面性，将对所有检索到的研究进行筛选，以将其纳入评价。为此任务开发布尔查询需要训练有素的信息专家的专业知识。但是，即使对于这些专家搜索者而言，查询公式也可能是困难而漫长的：尤其是在处理他们可能不了解的医学领域时。为此，在先前的工作中已经提出了信息专家用来表示布尔查询的方法的两种计算方法。这些改编可以通过提供查询开发的良好起点来帮助信息专家。然而，这些计算方法存在许多局限性，尚未进行比较。在这项研究中，我们解决了先前工作的局限性并评估了两者。我们发现，在两种计算适应之间，目标方法比仅用于查询制定的概念方法更有效，但是，概念方法为手动查询细化提供了更好的起点。这项工作有助于告知那些有助于系统地进行审查构建的建筑物搜索工具。目标方法比仅用于查询制定的概念方法更为有效，但是，概念方法为手动查询细化提供了更好的起点。这项工作有助于告知那些有助于系统地进行审查构建的建筑物搜索工具。目标方法比仅用于查询制定的概念方法更为有效，但是，概念方法为手动查询细化提供了更好的起点。这项工作有助于告知那些有助于系统地进行审查构建的建筑物搜索工具。