An Improved Association Rules Algorithm Based on Frequent Item Sets

作者：Yaqiong Jiang, Jun Wang · 发表于：Procedia Engineering · 年份：2011 · DOI：10.1016/j.proeng.2011.08.625 · 被引用次数：4 · 研究领域：Data Mining Algorithms and Applications、Rough Sets and Fuzzy Logic

In this paper, based on the concept of Apriori algorithm for frequent itemsets, adding the element vector, sub-rule and parent-rule, an improved algorithm about association rules mining is proposed. This method overcomes the lack of traditional association rule mining method. It mines the rules while generating the frequent item sets, so the mining efficiency has been improved well.