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基于位对象的最大频繁模式挖掘算法

Algorithm Based on Bit Objects for Mining Maximal Frequent Patterns
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摘要 提出了基于位对象的最大频繁模式挖掘算法.算法中,用位对象表示数据,并用位对象概念改进FP-Tree.用深度优先搜索策略,通过压缩数据库,并用位对象的特性简化模式支持度的计数,使挖掘时不需产生条件FP-Tree和候选项目集,以提高最大频繁模式的挖掘效率.实验结果验证了BFP-Miner的有效性. A new algorithm based on bit objects, BFP-Miner, for mining maximal frequent patterns was proposed. It uses the bit objects to express data and to improve the FP-Tree （frequent pattern tree）. The algorithm uses depth-first search strategy, and simplifies the support counting of frequent patterns with the characteristics of the bit objects and by compression of the database. Neither a conditional FP-Tree nor candidate patterns are generated during mining the maximal frequent patterns, so that the mining efficiency is increased. Experimental result verifies the efficiency of the BFP-Miner.
作者 杨君锐 张铁军 刘南艳
机构地区 西安科技大学计算机科学与技术系
出处 《西南交通大学学报》 EI CSCD 北大核心 2008年第4期488-493,共6页 Journal of Southwest Jiaotong University
基金 陕西省自然科学基金资助项目(2005F13) 陕西省教育厅专项科研基金资助项目(06JK248)
关键词 数据挖掘 关联规则 最大频繁模式 位对象 data mining association rule maximal frequent pattern bit object
分类号 TP311.13 [自动化与计算机技术—计算机软件与理论]
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参考文献8

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二级参考文献28

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西南交通大学学报
2008年 第4期

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