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arXiv 2402.08565cs.AIcs.HCcs.IR
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人工智能用于文献综述:机遇与挑战

Artificial Intelligence for Literature Reviews: Opportunities and Challenges

The Open University(开放大学);University of Milano Bicocca(米兰比可卡大学)

Francisco Bolanos, Angelo Salatino, Francesco Osborne, Enrico Motta

AI总结:

本文综述AI在系统性文献综述筛选与提取阶段的应用,通过涵盖23项传统功能和11项AI功能的框架评估21款工具,并分析11款基于大语言模型的新工具,指出趋势、挑战与未来方向。

摘要:

本手稿对人工智能(AI)在系统性文献综述(SLR)中的应用进行了全面综述。SLR是一种严谨且有条理的方法论,用于评估和整合关于特定主题的既有研究。目前已经开发了大量工具来辅助SLR流程并实现部分自动化。AI在该领域日益增强的作用显示出巨大潜力,可为研究人员提供更有效的支持,推动文献综述走向半自动生成。我们的研究关注AI技术如何应用于SLR的半自动化,特别是筛选和提取阶段。我们使用一个结合了23项传统功能与11项AI功能的框架,考察了21款主流SLR工具。我们还分析了11款近期工具,这些工具利用大型语言模型检索文献并辅助学术写作。最后,本文讨论了该领域的当前趋势,概述了关键研究挑战,并提出了未来研究方向。

英文摘要:

This manuscript presents a comprehensive review of the use of Artificial Intelligence (AI) in Systematic Literature Reviews (SLRs). A SLR is a rigorous and organised methodology that assesses and integrates previous research on a given topic. Numerous tools have been developed to assist and partially automate the SLR process. The increasing role of AI in this field shows great potential in providing more effective support for researchers, moving towards the semi-automatic creation of literature reviews. Our study focuses on how AI techniques are applied in the semi-automation of SLRs, specifically in the screening and extraction phases. We examine 21 leading SLR tools using a framework that combines 23 traditional features with 11 AI features. We also analyse 11 recent tools that leverage large language models for searching the literature and assisting academic writing. Finally, the paper discusses current trends in the field, outlines key research challenges, and suggests directions for future research.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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