基于差异节点集的加权频繁项集挖掘算法  

Weighted Frequent Itemsets Mining Algorithm Based on Difference Nodeset

作　　者：王斌 房新秀 魏天佑 WANG Bin;FANG Xinxiu;WEI Tianyou(School of Information and Control Engineering,Qingdao Universiy of Technology,Qingdao,Shandong 266520,China)

机构地区：[1]青岛理工大学信息与控制工程学院,山东青岛266520

出　　处：《计算机工程》2020年第5期150-156,共7页Computer Engineering

基　　金：国家自然科学基金(61502262)。

摘　　要：针对基于WN-list的加权频繁项集挖掘算法NFWI挖掘效率低的问题,提出一种基于WDiffNodeset的加权频繁项集挖掘算法DiffNFWI。对DiffNodeset数据结构进行扩展得到WDiffNodeset,采用集合枚举树和混合搜索策略相结合的方法查找加权频繁项集,以避免大量的交集运算并实现高效查找。使用差集策略计算项集的加权支持度,从而降低计算量。在mushroom、pumsb等数据集上的实验结果表明,DiffNFWI算法的运行效率优于NFWI算法。To address the low mining efficiency of NFWI,a WN-list based algorithm for weighted frequent itemsets mining,this paper proposes a WDiffNodeset-based weighted frequent itemsets mining algorithm,DiffNFWI.The algorithm extends the data structure of DiffNodeset to get WDiffNodeset,and then combines set enumeration tree with hybrid search strategy to find the weighted frequent itemsets,so as to reduce intersection operations and achieve efficient search.The difference set strategy is used to calculate the weighted support degree of the itemsets to reduce the amount of calculation.Experimental results show that the efficiency of the DiffNFWI algorithm is better than that of the NFWI algorithm on mushroom,pumsb and other datasets.

关 键 词：加权频繁项集 加权支持度 集合枚举树 混合搜索策略 差集策略 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]