Automation of systematic literature reviews: A systematic literature review

被引:169
作者
van Dinter, Raymon [1 ]
Tekinerdogan, Bedir [1 ]
Catal, Cagatay [2 ]
机构
[1] Wageningen Univ & Res, Informat Technol Grp, Wageningen, Netherlands
[2] Qatar Univ, Dept Comp Sci & Engn, Doha, Qatar
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
Systematic literature review (SLR); Automation; Review; Text mining; Machine learning; Natural language processing; DATA EXTRACTION; FULL-TEXT; SUPPORT; WORKLOAD; ERRORS; TOOLS;
D O I
10.1016/j.infsof.2021.106589
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Context: Systematic Literature Review (SLR) studies aim to identify relevant primary papers, extract the required data, analyze, and synthesize results to gain further and broader insight into the investigated domain. Multiple SLR studies have been conducted in several domains, such as software engineering, medicine, and pharmacy. Conducting an SLR is a time-consuming, laborious, and costly effort. As such, several researchers developed different techniques to automate the SLR process. However, a systematic overview of the current state-of-the-art in SLR automation seems to be lacking. Objective: This study aims to collect and synthesize the studies that focus on the automation of SLR to pave the way for further research. Method: A systematic literature review is conducted on published primary studies on the automation of SLR studies, in which 41 primary studies have been analyzed. Results: This SLR identifies the objectives of automation studies, application domains, automated steps of the SLR, automation techniques, and challenges and solution directions. Conclusion: According to our study, the leading automated step is the Selection of Primary Studies. Although many studies have provided automation approaches for systematic literature reviews, no study has been found to apply automation techniques in the planning and reporting phase. Further research is needed to support the automation of the other activities of the SLR process.
引用
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页数:16
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