Applying data mining techniques for discovering association rules

Meiho University Institutional Repository > 經營管理學院 > 企業管理系 > 期刊論文 > Item 987654321/3787

jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://ir.meiho.edu.tw/ir/handle/987654321/3787

题名:	Applying data mining techniques for discovering association rules
作者:	Huang, Mu-Jung Sung, Hsiu-Shu Hsieh, Tsu-Jen Wu, Ming-Cheng Chung, Shao-Hsi
贡献者:	經營管理學院
关键词:	Data mining · association rule mining (ARM) chronic diseases
日期:	2019
上传时间:	2019-12-04T01:48:30Z (UTC)
摘要:	Data mining has become a hot research topic, and how to mine valuable knowledge from such huge volumes of data remains an open problem. Processing huge volumes of data presents a challenge to existing computation software and hardware. This study proposes a model using Association Rule Mining (ARM) which is a kind of data mining techniques for discovering association rules of chronic diseases from the enormous data that are collected continuously through health examination and medical treatment. This study makes three critical contributions: (1) it suggests a systematical model of exploring huge volumes of data using ARM, (2) it shows that helpful implicit rules are discovered through data mining techniques, and (3) the results proved that the proposed model can act as an expert system for discovering useful knowledge from huge volumes of data for the references of doctors and patients to the specific chronic diseases prognosis and treatments.
显示于类别:	[企業管理系] 期刊論文

文件中的档案:

档案	描述	大小	格式	浏览次数
Applying data mining techniques for discovering association rules.pdf		491Kb	Adobe PDF	0	检视/开启

检视Licence

在MUIR中所有的数据项都受到原著作权保护.