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基于概念格和Apriori的关联规则挖掘算法分析
引用本文:王德兴,胡学钢,刘晓平,王浩. 基于概念格和Apriori的关联规则挖掘算法分析[J]. 合肥工业大学学报(自然科学版), 2006, 29(6): 699-702
作者姓名:王德兴  胡学钢  刘晓平  王浩
作者单位:合肥工业大学,计算机与信息学院,安徽,合肥,230009;合肥工业大学,计算机与信息学院,安徽,合肥,230009;合肥工业大学,计算机与信息学院,安徽,合肥,230009;合肥工业大学,计算机与信息学院,安徽,合肥,230009
基金项目:中国科学院资助项目 , 安徽省自然科学基金
摘    要:概念格通过概念的内涵和外延及泛化和例化之间的关系来表示知识,因而适用于从数据库中挖掘规则的问题描述;在概念格的内涵中引入等价关系并将其外延量化,得到量化概念格;利用量化概念格挖掘关联规则,与采用Apriori算法计算频繁项目集获取关联规则相比较,不需要计算频繁项目集,容易获得用户感兴趣的关联规则,同时减少了大量冗余的规则,提高了挖掘效率。

关 键 词:关联规则  Apriori算法  概念格  数据挖掘
文章编号:1003-5060(2006)06-0699-04
修稿时间:2005-06-06

Analysis of association rule mining algorithms based on the concept lattice and the Apriori algorithm
WANG De-xing,HU Xue-gang,LIU Xiao-ping,WANG Hao. Analysis of association rule mining algorithms based on the concept lattice and the Apriori algorithm[J]. Journal of Hefei University of Technology(Natural Science), 2006, 29(6): 699-702
Authors:WANG De-xing  HU Xue-gang  LIU Xiao-ping  WANG Hao
Abstract:A concept lattice represents knowledge by the relation between the intension and extension of a concept and the relation between the generalization and specialization of a concept,thus it is applied to the description of association rules mining in databases.The Quantitative Concept Lattice(QCL),which evolves from the concept lattice by introducing equivalence relation to its intension and quantity to its extension,can be used to mine the association rules the users are interested in.In comparison with the Apriori algorithm,with the QCL,the frequent item sets need not be calculated,then a great many of redundant association rules are reduced,and the efficiency of association rules mining is improved.
Keywords:association rule  Apriori algorithm  concept lattice  data mining
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