基于序列模式的正负关联规则研究

基于序列模式的正负关联规则研究

郭跃斌,翟延富,董祥军*,杨越越,李刚

山东轻工业学院信息科学与技术学院, 山东济南 250353

收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2006-10-24 发布日期:2006-10-24
通讯作者: 郭跃斌

Positive and negative association rules based on sequential patterns

GUO Yue-bin,ZHAI Yan-fu,DONG Xiang-jun,YANG Yue-yue,LI Gang

Department of Computer Science and Technology, Shandong Institute of Light Industry, Jinan 250353, Shandong, China

Received:1900-01-01 Revised:1900-01-01 Online:2006-10-24 Published:2006-10-24
Contact: GUO Yue-bin

摘要/Abstract

摘要： 序列模式可预测企业的发展方向，负关联规则可展现不良因素的根源，序列模式的正负关联规则为企业决策提供更全面的信息. 将序列模式和负关联规则的挖掘算法相结合，利用项集间的相关性，挖掘出序列模式的正负关联规则.

关键词: 序列模式, 正关联规则, 相关性 , 负关联规则

Abstract: Sequential patterns can predict company developing trends. The negative association rules can show the origin of bad factors, and the positive and negative association rules based on sequential patterns can offer more comprehensive information. The mining of the positive and negative association rules based on sequential patterns was given by combining the sequential patterns algorithm and the negative association rules algorithm and utilizing the correlation between item sets.

Key words: correlation , the negative association rules, the positive association rules, sequential pattern

中图分类号:

TP311

郭跃斌,翟延富,董祥军*,杨越越,李刚 . 基于序列模式的正负关联规则研究[J]. J4, 2007, 42(9): 88-90 .

GUO Yue-bin,ZHAI Yan-fu,DONG Xiang-jun,YANG Yue-yue,LI Gang . Positive and negative association rules based on sequential patterns[J]. J4, 2007, 42(9): 88-90 .

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