关联规则挖掘AprioriTid算法的改进  

Improvement of AprioriTid algorithm for mining association rules

作　　者：彭仪普[1] 熊拥军[2] 

机构地区：[1]武汉大学测绘遥感信息工程国家重点实验室,湖北武汉430079 [2]中南大学铁道学院,湖南长沙410075

出　　处：《计算机应用》2005年第5期979-981,共3页journal of Computer Applications

基　　金：国家自然科学基金资助项目项目(40001017);霍英东教育基金会青年教师基金资助项目(71017)

摘　　要：提出了一种将AprioriTid算法与事务压缩和项目压缩相结合的改进算法。该算法中候选项目集及支持度计算是在每条事务压缩后通过联接产生,候选项目集采用关键字识别,省去了AprioriTid算法中的剪枝和字符串模式匹配步骤。实验结果表明,改进的算法执行效率明显优于AprioriTid算法。An enhanced algorithm associating AprioriTid with transaction reduction and item reduction technique was put forward. In the algorithm candidate set generation and the support calculation of each itemset were created after each transaction was compressed and connected, and the key word identifying was adopted in the candidate set, thus the process of pruning and string pattern matching was removed from AprioriTid algorithm. Testing results showed that the algorithm clearly outperformed AprioriTid algorithm.

关 键 词：数据挖掘 关联规则 APRIORITID算法 事务压缩 项目压缩 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]