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.
出处
《计算机应用》
CSCD
北大核心
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)
