摘要
关联规则的采掘是数据采掘研究的一个重要方面 .分析现有的关联规则采掘算法中所存在的问题 :首先是关联规则在其表达形式上没有考虑各种可能的反面示例的影响 ,因而导致知识表达功能的不够完善 ;其次是有可能一条规则即使可信度和支持度都很高 ,仍没有实际意义 ,甚至是误导性的 .因此对关联规则的形式定义作了修改 ,将运用差异思想引入的兴趣度阈值运用到关联规则中来 ,并给出其形式定义 .在分析了兴趣度的实际意义以后 ,讨论了兴趣度与概念层次的结合 .
Mining the association rules is an important aspect of the study of data mining. This paper analyzes some problems existing in those available association rules mining algorithms. Firstly, association rules neglect the effect of all kinds of potential negative examples, which results in imperfection in their expressive ability; secondly, it is probable that a rule will have no practical significance or even be misleading even if it possesses high confidence and support. The paper revises the formal definition of association rules, makes use of the deviation based interest value presented in association rules, and defines it in form. In addition to analyzing the practical significance of the interest value, the combination of the interest value and concept hierarchy are also discussed.
出处
《计算机研究与发展》
EI
CSCD
北大核心
2000年第5期627-633,共7页
Journal of Computer Research and Development
基金
国家自然科学基金和国家"八六三"高技术研究发展计划基金资助!(项目编号 863 -3 0 6-ZT0 2 -0 5 -1)
关键词
数据采掘
关联规则
兴趣度
概念层次
阈值
数据
data mining, association rules, interest measure, concept hierarchy
