• DocumentCode
    2138258
  • Title

    Many-to-one mapping: The principle of Chinese medicinal property theory learned from strong association rules

  • Author

    Rui Jin ; Chun-miao Xue ; Li-li Wu ; Bing Zhang ; Qian Lin ; Sen-mao Liu

  • Author_Institution
    Sch. of Chinese Materia Medica, Beijing Univ. of Chinese Med., Beijing, China
  • fYear
    2013
  • fDate
    23-25 July 2013
  • Firstpage
    951
  • Lastpage
    956
  • Abstract
    Knowledge discovery in databases is believed to be a promising technique in the modernization of Traditional Chinese Medicine (TCM), especially for understanding the mysterious TCM theory. Based on the classic literature resources, this paper mined the association rules between the Chinese medicinal property (nature or flavor) and the practical efficacy by the Apriori algorithm. The results showed strong associations between a series of efficacy attributes and the specific medicinal property manifestly, which we defined as a kind of many-to-one mapping. It showed that the same property of different medicinal herbs might be inferred from distinct origins and reflected in different ways. It was believed as the inherent principle of the Chinese Medicinal Property Theory, which would help to understand the essence of the TCM medical system.
  • Keywords
    data mining; medical computing; medicine; Apriori algorithm; Chinese medicinal property; Chinese medicinal property theory; TCM medical system; TCM theory; knowledge discovery; many-to-one mapping; medicinal herbs; strong association rules; traditional Chinese medicine; Association rules; Curing; Data models; Databases; Educational institutions; Market research; Chinese medicinal property theory; Traditional Chinese Medcine; association rules mining; knowledge discovery; many-to-one;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2013 Ninth International Conference on
  • Conference_Location
    Shenyang
  • Type

    conf

  • DOI
    10.1109/ICNC.2013.6818113
  • Filename
    6818113