关于"合法"文本和数据挖掘的文献综述
1Law, University of Cyprus, Nicosia, Nicosia, Cyprus.
Open research Europe
|November 6, 2024
概括
文本和数据挖掘 (TDM) 对于发现数据中隐藏的模式至关重要. 然而,在复杂而不断变化的合法TDM法律环境中导航需要一种统一的方法来理解当前的法规.
科学领域:
- 计算社会科学 计算社会科学
- 法律信息学 法律信息学
- 数据科学数据科学数据科学
背景情况:
- 文本和数据挖掘 (TDM) 是一个越来越重要的自动化过程,用于在大数据集中的模式发现.
- 它的应用涵盖了包括医学和商业在内的多个行业,推动了数据驱动的解决方案.
- 现有的监管框架往往不适合TDM,导致法律模两可.
研究的目的:
- 对学术界和实践者对合法TDM的看法进行整体评估.
- 分析有关TDM监管框架的碎片化文献.
- 确定TDM监管中的关键类别和挑战.
主要方法:
- 在文献综述中采用了基于理论的方法.
- 分析了88篇有关合法TDM的文献.
- 识别和分析与TDM监管相关的7个不同的类别.
主要成果:
- 关于TDM监管的文献是零碎的,提供对合法实践的零碎见解.
- 从学术和实践者的观点分析中,出现了七个关键类别.
- 目前适用于TDM用户的监管框架是多方面的,并取决于环境.
结论:
- 对于对TDM法规进行整体解释的需求显著且越来越大.
- 需要一个全面的指南或"地图"来帮助用户浏览TDM的复杂法律规则.
- 随着TDM的不断变化的性质,需要适应和明确的监管指导.
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