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基于时序向量聚类的周期关联规则发现算法
引用本文:罗兰,曾斌.基于时序向量聚类的周期关联规则发现算法[J].计算机工程,2010,36(19):110-112.
作者姓名:罗兰  曾斌
作者单位:1. 浙江大学计算机学院,杭州,310027;浙江林学院信息工程学院,浙江,临安,311300
2. 浙江林学院信息工程学院,浙江,临安,311300
基金项目:浙江省自然科学基金资助项目,浙江省科技厅科技计划基金资助项目 
摘    要:针对目前周期关联规则难以划分时间区域和基础算法效率低等问题,提出一种基于周期关联规则的发现算法(CARDSATSV)。采用由项目支持度组成的时序向量作为时域数据特征点进行聚类,用DB Index准则控制聚类个数以达到最佳的聚类效果。给出CFP-tree算法来发现周期关联规则,利用基于条件FP-tree 的周期性剪裁技术提高算法效率。实验表明,和目前周期关联规则发现算法相比,CARDSATSV可以发现更多有用的周期关联规则,时空效率有一定的提高。

关 键 词:时序向量  强周期关联规则  差异序列法  周期FP-tree算法  差异序列聚类算法

Discovering Arithmetic of Cyclic Association Rules Based on Time Series Vector Clustering
LUO Lan,ZENG Bin.Discovering Arithmetic of Cyclic Association Rules Based on Time Series Vector Clustering[J].Computer Engineering,2010,36(19):110-112.
Authors:LUO Lan  ZENG Bin
Affiliation:1. College of Computer, Zhejiang University, Hangzhou 310027, China; 2. School of Information Engineering, Zhejiang Forestry University, Lin'an 311300, China)
Abstract:The existing cyclic association rules have disadvantage to compartmentalize a cycle into several time segments and the base arithmetic disadvantage is low-level efficiency etc. This paper presents CARDSATSV. It chooses the time sequence vector which consists of the support of item to cluster, and uses DB Index to determine the optimal class number of cluster. It brings forward Cyclic FP-tree(CFP-tree) to discover cyclic association rules. CFP-tree handle cycle clipping technology is based on conditional FP-tree to improve efficiency. Experiments show that CARDSATSV can discover more useful cyclic association rules and can improve efficiency, compared with the existing cyclic association rules.
Keywords:time series vector  lusty cyclic association rules  difference sequence arithmetic  Cyclic FP-tree(CFP-treee) algorithm  clustering arithmetic based on difference sequence
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