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基于交易数据库的关联规则生成算法FAS及其应用
引用本文:刘萍,别荣芳. 基于交易数据库的关联规则生成算法FAS及其应用[J]. 计算机应用, 2005, 25(6): 1376-1378,1381
作者姓名:刘萍  别荣芳
作者单位:中国人民大学,网络与教育技术中心,北京,100872;北京师范大学,信息科学学院,北京,100875Z
基金项目:国家自然科学基金资助项目(60273015,10001006)
摘    要:生成关联规则算法FAS,能够迅速区分某频繁项集的所有关联规则的前件和后件,生成给定频繁项目集的关联规则。基于FAS算法,设计并实现了一个基于最近挖掘结果的数据挖掘系统AR—Miner。该系统主要包括数据预处理、频繁集初始计算、频繁集更新计算、频繁集选择、关联规则生成五部分,不仅实现了关联规则挖掘的可视化和生成结果按“支持度一可信度”形式的可视化,还为基于频繁集的交互式挖掘提供了方便、友好的界面。

关 键 词:数据挖掘  关联规则  频繁项集
文章编号:1001-9081(2005)06-1376-03

Association rules mining algorithm FAS and it's application
LIU Ping,BIE Rong-fang. Association rules mining algorithm FAS and it's application[J]. Journal of Computer Applications, 2005, 25(6): 1376-1378,1381
Authors:LIU Ping  BIE Rong-fang
Affiliation:LIU Ping 1,BIE Rong-fang 21. Network Center,Renmin University of China,Beijing 100872,China, 2. College of Information Science,Beijing Normal University,Beijing 100875,China)
Abstract:An association rules mining alogorithm FAS was proposed . It rapidly distinguishes in a certain frequent itemset all the formers and the latters which were used to generate association rules. A FAS-based data mining system AR_Miner with the latest mining results were also designed. It consists of five parts: Data Preprocessing, Initial calculation of frequent itemsets, Update calculation of frequent itemsets, Choice of frequent itemsets and generation of association rules. It not only visualized generated results in support-confidence form, but also provided an easily accessible and user-friendly interface for interactive mining based on frequent itemsets.
Keywords:data mining  association rules  frequent itemsets
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