摘要
在支持度和置信度不变的情况下,随机或偶然向数据集添加数据记录会导致关联规则的变化.在FUP算法的基础上给出了一个改进的增量式更新算法,本算法在充分利用先前关联规则的基础上极大的减少了扫描原数据集的次数,与FUP算法相比极大的减少了算法运行时间,并实验验证了算法的优越性.
Under the situation of support and confidence unchanged, inserting data record randomly or accidentally will change the association rules. This paper gives an improved incremental updating algorithm based on the FLIP algorithm, which greatly decreases times of scanning database by making use of the precious association rules. Comparing with the FLIP algorithm the algorithm decreases the of operating time. The experiment shows the superiority of this algorithm.
出处
《沈阳师范大学学报(自然科学版)》
CAS
2006年第1期51-54,共4页
Journal of Shenyang Normal University:Natural Science Edition
基金
辽宁省教育厅资助项目(202112020)
关键词
数据挖掘
关联规则
增量式更新算法
频繁项目集
data mining
association rules
incremental updating algorithm
large items