dc.contributor.author 胡慧蓉 dc.contributor.author 王周敬 dc.date.accessioned 2017-11-14T01:29:22Z dc.date.available 2017-11-14T01:29:22Z dc.date.issued 2005-07-10 dc.identifier.citation 计算机应用,2005,(07):107-109 dc.identifier.issn 1001-9081 dc.identifier.other JSJY200507032 dc.identifier.uri https://dspace.xmu.edu.cn/handle/2288/142446 dc.description.abstract 首先对关联规则挖掘问题进行了简单的回顾,然后应用关系理论思想,引入了项目可辨识向量及其“与”运算,设计了一种快速挖掘算法SLIG,将频繁项目集的产生过程转化为项目集的关系矩阵中向量运算过程。算法只需扫描一遍数据库,克服了Apriori及其相关算法产生大量候选集和需多次扫描数据库的缺点。实验证明,与Apriori算法相比,SLIG算法提高了挖掘效率。 dc.description.abstract After the introduction of famous Apriori algorithms, an efficient algorithm SLIG(Single-level Large Itemsets Generation) learning from relation theory and "AND" operation on recognizable vectors was proposed. SLIG transformed the production process of frequent itemset to the vector calculation process in relationship matrix and only needed to scan the database once. Empirical evaluation and experiments show that SLIG is more efficient than the algorithms that need to pass the large database many times. dc.language.iso zh_CN dc.subject 关联规则 dc.subject 频繁集 dc.subject 可辨识向量 dc.subject 可辨识矩阵 dc.subject association rule dc.subject frequent itemset dc.subject recognizable vectors dc.subject recognizable matrix dc.title 一种基于关系矩阵的关联规则快速挖掘算法 dc.title.alternative Fast algorithm for mining association rules based on relationship matrix dc.type Article
﻿