Exploring Associated Networks of Cold Herb and Hot Herb within the Framework of Traditional Chinese Medicine through Text Mining

被引:0
作者
Liang, Fei [1 ]
Zhan, Junping [2 ,3 ]
Zheng, Guang [2 ,4 ]
Jiang, Miao [2 ]
Lu, Cheng [2 ]
Lu, Aiping [2 ]
机构
[1] Beijing Univ Chem Technol, Beijing 100029, Peoples R China
[2] China Acad Chinese Med Sci, Inst Bas Res Clin Med, Beijing 100700, Peoples R China
[3] Shanghai Univ Tradit Chinese Med, Shanghai 201203, Peoples R China
[4] Lanzhou Univ, Sch Informat Sci Engn, Lanzhou 730000, Gansu, Peoples R China
来源
2012 6TH INTERNATIONAL CONFERENCE ON NEW TRENDS IN INFORMATION SCIENCE, SERVICE SCIENCE AND DATA MINING (ISSDM2012) | 2012年
基金
中国博士后科学基金; 美国国家科学基金会;
关键词
traditional Chinese medicine; cold herb; hot herb; network; text mining; DATA SLICING ALGORITHM;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
It is an interesting and meaningful thing to explore the associated networks between cold herb and hot herb within the framework of traditional Chinese medicine because they might be useful for both clinical practice and scientific research. In this study, focused on the fields of disease, pattern/syndrome, symptom, and decoction, we constructed the associated networks between cold herb and hot herb. By analyzing these networks, we found that there is no clear separation between cold herb and hot herb. What's more, they have mutual parts among their networks on disease, pattern/syndrome, symptom, and decoction.
引用
收藏
页码:344 / 347
页数:4
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