摘要
目的针对时间效率不高的问题,对利用属性特性挖掘粒关联规则的算法进行改进。方法在分析粒计算有关定义和原有算法思想的基础上,调整原有算法的相关流程顺序,同时设置相关标志位避免对部分数据集重复组织包含关系的操作。结果通过相关实验证明,有关改进有效减少了算法所需操作步骤,降低了时间消耗。结论通过调整流程顺序和设置标志位的方法 ,有效减少了原有算法的挖掘时间,具有一定实用性。
Purposes —To improve the algorithm of mining granular association rules by using attribute characteristics in terms of its time efficiency. Methods —After the analysis of the relevant definitions of granular computing and the original algorithm, its sequence of related process is adjusted. And the related flag bits are set up to avoid the repetition of the inclusive relationship of the partial data sets. Results —The relevant experiments show that the improved algorithm can effectively reduce the operation steps and time under the premise of the mining accuracy. Conclusions — The mining time of the original algorithm can be effectively reduced by adjusting the sequence of process and other methods.
作者
邱京伟
QIU Jing-wei(College of Information ＆ Electrical Engineering,Ningde Normal University,Ningde 352100,Fujian,China)
出处
《宝鸡文理学院学报（自然科学版）》
CAS
2018年第3期61-64,共4页
Journal of Baoji University of Arts and Sciences(Natural Science Edition)
基金
福建省中青年教师教育科研项目(JAT160529)
宁德师范学院2015年校级科研项目(2015Q12)
关键词
粒关联规则
时间消耗
挖掘效率
属性
改进
granular association rules
time consumption
mining efficiency
attribute
improvement
