A Systematic Literature Review in Causal Association Rules Mining

Shkurte Luma-Osmani, F. Ismaili, Xhemal Zenuni, Bujar Raufi
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引用次数: 3

Abstract

As quoted recently, this is the age of information, and for information we need data. Data is everywhere around us and it is expanding dramatically. The aim of this research is to inspect and summarize the state-of-the-art approaches and studies of machine learning methods to causal inference techniques. This review utilizes a systematic literature research to the mostly prominent digital database libraries in the field of computer sciences in recent years. The objective is to identify and investigate three raised research questions to broadly analyze and detailly explore several points of view concerning causal association rules and their application in real-world problems.
因果关联规则挖掘的系统文献综述
正如最近引用的,这是一个信息时代,而为了获取信息,我们需要数据。数据无处不在,而且还在急剧增长。本研究的目的是检查和总结机器学习方法对因果推理技术的最新方法和研究。本文对近年来计算机科学领域最突出的数字数据库图书馆进行了系统的文献研究。目的是确定和调查提出的三个研究问题,以广泛分析和详细探索有关因果关联规则及其在现实世界问题中的应用的几个观点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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