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A comparison of automatic Boolean query formulation for systematic reviews

机译:自动布尔查询制度进行系统评论的比较

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摘要

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.
机译:系统评价是全面的文学评论,目标是一个高度集中的研究问题。在医疗领域,复杂的布尔查询用于识别研究。为了确保全面性,检索的所有研究都被筛选出纳入或排除在审查中。为此任务开发布尔查询需要培训的信息专家的专业知识。但是,即使对于这些专家搜索者,查询制剂也可能是困难和冗长的:特别是在处理他们可能不了解的药物区域时。为此,已经提出了在事先工作中提出了两种方法信息专家使用来制定布尔查询的两个计算调整。这些调整可用于通过为查询开发提供良好的起点来帮助信息专家。但是,已经提出了许多具有这些计算方法的局限性,并且尚未进行它们之间的比较。在这项研究中,我们解决了以前的工作的局限性并评估了这两项。我们发现,在两个计算自适应之间,目标方法比单独的查询制剂的概念方法更有效,然而,概念方法为手动查询细化提供了更好的起点。这项工作有助于通知那些辅助系统审查建设的建筑搜索工具。

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