Construction of Multidimensional Data Knowledge Base by Improved Classification Association Rule Mining Algorithm

被引：0
|
作者：
Tan, Qing [1 ]
机构：
[1] Luoyang Normal Univ, Coll Informat Technol, Luoyang 471934, Henan, Peoples R China
来源：
PROCEEDINGS OF THE 2016 7TH INTERNATIONAL CONFERENCE ON EDUCATION, MANAGEMENT, COMPUTER AND MEDICINE (EMCM 2016) | 2017年 / 59卷
关键词：
Multidimensional data; Knowledge base; Association rule; Classification; FP-Growth;
D O I：
暂无
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
Firstly, this paper analyzes the advantages and disadvantages of the existing association rules mining algorithm, and gives the method of multidimensional data analysis. In order to remedy the defects, this paper discusses and improves clustering and classification algorithm for constructing intelligent knowledge base. The paper presents construction of multidimensional data knowledge base by improved classification association rule mining algorithm. The effectiveness of the proposed method is analyzed by an example.
引用
收藏
页码：901 / 905
页数：5
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