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分段支持度Apriori算法及应用
引用本文:张春生,宋琳琳.分段支持度Apriori算法及应用[J].计算机工程与应用,2010,46(16):157-159.
作者姓名:张春生  宋琳琳
作者单位:内蒙古民族大学 计算机科学与技术学院,内蒙古 通辽 028043
基金项目:内蒙古人才基金资助项目(第8批),内蒙古教育科研项目 
摘    要:首先指出单支持度的Apriori算法的局限性,分析了目前为克服单支持度Apriori算法的局限性而提出的多支持度的Apriori算法的不完备性,针对事务中的一些潜在规则,提出了一种分段支持度Apriori算法。算法不是简单地对经典Apriori算法进行扩展或改进,而是从理论上破坏了Apriori算法全局、高频两个性质,采用分段支持度的方法对数据库进行数据挖掘,可以发现经典和多支持度Apriori算法不能发现或很难发现的强关联规则,并以较快的速度得以实现。

关 键 词:分段  支持度  Apriori算法  群体特征  数据挖掘  
收稿时间:2008-11-21
修稿时间:2009-2-23  

Sub-support Apriori algorithm and its application
ZHANG Chun-sheng,SONG Lin-lin.Sub-support Apriori algorithm and its application[J].Computer Engineering and Applications,2010,46(16):157-159.
Authors:ZHANG Chun-sheng  SONG Lin-lin
Affiliation:College of Computer Science and Technology,Inner Mongolia University for Nationalities,Tongliao,Inner Mongolia 028043,China
Abstract:Firstly,this paper indicates the localization of single-support Apriori algorithm,and analyzes the imperfection of multiple supports Apriori algorithm that is proposed for overcoming the localization of single-support Apriori algorithm.Aiming at some latent rules of affair,the paper proposes a sub-support Apriori algorithm.It does not simply expand or improve the classical Apriori algorithm.The proposed algorithm destroys Apriori algorithm's qualities—global and high frequency in theory,and uses the method of sub-support to data mining for the database.It discovers that classical and multiple supports Apriori algorithm are difficult to find the strong relevancy regulation.The proposed algorithm can be realized for a quick speed.
Keywords:subsection  support  Apriori algorithm  colony character  data mining
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