Abstract: This paper presents a weighted frequent k-itemset generation algorithm based on bit matrix. The algorithm introduces the concept of weighted support degree and minimum support expectation. It only scans the database once, prunes the weighted frequent k-itemset generation process based on the 2-itemset bit matrix by constructing filtering condition and improves the generation efficiency of weighted frequent itemset.

Key words: weighted association rule, minimum support expectation, frequent itemset

摘要： 提出一种基于位矩阵的加权频繁k项集生成算法。该算法引入加权支持度和最小支持期望的概念，对数据库仅进行一次扫描，通过构建筛选条件对基于频繁2项集位矩阵的加权频繁k项集生成过程进行剪枝，有效提高了加权频繁项集的生成效率。

关键词: 加权关联规则, 最小支持期望, 频繁项集

CLC Number: 

• TP301.6