挖掘多关系关联规则

Mining of Multi-Relational Association Rules

关联规则的挖掘是数据挖掘中的一项重要和基础的技术,已进行了多方面的深入研究,有着广泛的应用.传统数据挖掘算法是针对单表数据进行处理的,在应用于多关系数据挖掘时存在诸多问题.对多关系关联规则的挖掘问题进行了重新定义和总结.提出了多关系关联规则挖掘的一个框架,并对已有算法进行了分类.然后对各类代表性算法进行了描述、分析和对比,对尚存在的问题进行了分析和总结.最后,对该领域未来的研究工作提出了建议.

Association rule mining is one of the most important and basic technique in data mining, which has been studied extensively and has a wide range of applications. However, as traditional data mining algorithms usually only focus on analyzing data organized in single table, applying these algorithms in multi-relational data environment will result in many problems. This paper summarizes these problems, proposes a framework for the mining of multi-relational association rule, and gives a definition of the mining task, After classifying the existing work into two categories, it describes the main techniques used in several typical algorithms, and it also makes comparison and analysis among them. Finally, it points out some issues unsolved and some future further research work in this area.