一种多最小支持度加权关联规则挖掘算法  

Algorithm of Mining Weighted Association Rules with Multiple Minimum Supports

作　　者：张争龙[1] 李星毅[1] 

机构地区：[1]江苏大学计算机科学与通信工程学院,镇江212013

出　　处：《科学技术与工程》2013年第19期5687-5691,共5页Science Technology and Engineering

基　　金：国家自然科学基金(10972027);十一五国家科技支撑计划(2006BAG01A0);江苏大学校基金(11JDG064)资助

摘　　要：针对实际交易数据库中,不同项目的重要性和出现概率各不相同的两个问题,提出一种基于等价类和多最小支持度的加权关联规则算法,从而挖掘出那些覆盖较少数据但却有意义、用户可能更感兴趣的关联规则。算法按照项目的最小支持度升序对交易记录进行等价类划分,然后按照项目的最小支持度降序依次求出每一等价类内的加权频繁项集。算法采用垂直数据库的数据表示形式,挖掘过程中避免了对数据库的重复扫描。对比实验结果证明,改进算法具有良好的挖掘性能。Algorithm of mining weighted association rules based on equivalence classes and multiple minimum supports is proposed to solve the problem that the transactions and data items have not the same importance and fre- quency in datasets. The algorithm allows the user to specify varied minimum supports and gives items weights to find association rules those cover less data but are useful, in which the user are more interested. The algorithm di- vides the items into different equivalence classes in the ascending order of their MIS （ minimum item supports） val- ues, and then mines the weighted frequent itemsets in each class respectively in the descending order of the mini- mum support of items. Moreover, the algorithm adopts vertical database to represent primitive transactional database and there is no need to scan the database repeatedly. The experimental results show that the proposed algorithm is efficient.

关 键 词：数据挖掘 多最小支持度 加权关联规则 等价类 垂直数据库 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]