摘要
本文提出了一种基于图的关联规则挖掘的改进算法。首先介绍了基于图的关联规则挖掘算法;然后,在此基础上对原算法进行了修改,通过在图中查找完全子图来寻找频繁项集;最后,对原算法、改进算法和Apriori算法的优缺点进行了简单的比较分析。
In this paper we present an improved graph-based algorithm for discovering association rules. Firstly, the graph-based algorithm for discovering association rules is discussed. Then, based on it, this paper modifies the former algorithm, and the large itemsets can be generated through discovering the clique graphs in the association graph. Finally, we compare the improved algorithm with the former algorithm and the Apriori algorithm.
出处
《计算机工程与科学》
CSCD
2005年第5期48-51,共4页
Computer Engineering & Science
