Association rule mining is intended for searching for the relationships between attributes in transaction databases. The whole process of rule discovery is very complex, and involves pre-processing techniques, a rule mining step, and post-processing, in which visualization is carried out. Visualization of discovered association rules is an essential step within the whole association rule mining pipeline, to enhance the understanding of users on the results of rule mining. Several association rule mining and visualization methods have been developed during the past decades. This review paper aims to create a literature review, identify the main techniques published in peer-reviewed literature, examine each method's main features, and present the main applications in the field. Defining the future steps of this research area is another goal of this review paper.

翻译：关联规则挖掘旨在探索事务数据库中属性之间的关联关系。规则发现的全过程极为复杂，涉及预处理技术、规则挖掘步骤及后处理环节（其中可视化在此阶段实施）。对已发现的关联规则进行可视化是关联规则挖掘流程中的关键步骤，有助于提升用户对规则挖掘结果的理解。过去数十年间，研究者已开发出多种关联规则挖掘与可视化方法。本文旨在通过文献综述，识别同行评审文献中发布的主要技术，分析各方法的核心特征，并呈现该领域的主要应用场景。此外，界定该研究领域未来发展方向亦是本文的另一目标。