计算机科学 ›› 2012, Vol. 39 ›› Issue (4): 159-163.

• 数据库与数据挖掘 • 上一篇    下一篇

依赖ER模型的多关系频繁模式发现方法

刘波   

  1. (暨南大学计算机科学系 广州510632)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Multi-relational Frequent Pattern Mining Method Relying on the ER Data Model

  • Online:2018-11-16 Published:2018-11-16

摘要: 为了解决多关系频繁模式挖掘面临的统计偏抖问题和效率问题,提出了基于ER(实体一联系)概念模型的方 法。其以ER模型的联系集为核心,利用扩展的关系数据库SQL统计原语,在用户给定数据约束和兴趣度约束的情 况下,减少多关系频繁模式的产生数量,既不需要将相关关系表做物理连接,也不会产生统计偏抖。与相关研究工作 的比较,说明了利用关系数据库管理系统和ER模型实现多关系频繁模式挖掘的有效性及正确性。

关键词: 数据挖掘,多关系,ER模型,频繁项集

Abstract: In order to solve statistical skew and efficiency problems, it presented a method based on the ER(Entity-Rela- tionship) concept model. hhe method takes relationship sets of an ER model as the core, and applies expanded SQI_ sta- tistical primitives of relational databases to produce multi-relational frequent patterns based on data and interestingness constraints which are provided by users, such that the patterns' number may be greatly reduced. Not only no physical joining of relational tables is needed, but also no statistical skew is produced. hhe comparison with some related research works explains the effectiveness and correctness of the method, which is performed by making use of the relational data- base management system and the ER model.

Key words: Data mining, Multi-relation, ER model, Frequent pattern

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