Information Analysis of Ancient Chinese Medicine Literatures Document-Keywords to Retrieve Text-Paragraph

[[abstract]]The development of traditional Chinese medicine for many years the history of the ancestors of Chinese medicine as a very valuable experience in the use of medical wisdom, modern medicine has become an important reference. Leap forward in information and computer, it is the ancient Chinese medicine into the digital information to your computer and save the best results fast query. However, a large number of ancient Chinese medicine literature information allows users to cause confusion, in the scattered literature of the ancient Chinese medicine to identify the paragraphs of information the user needs is the main purpose of this study. Source of this study is the use of "Compendium of Materia Medica" (Ming. Li), "seeking truth and herbal medicine" (the Qing Dynasty. Embroidered yellow palace), "Shen Nong's Herbal Classic" (the Han Dynasty. Author Yi) 3 written materials "category Bencao "Ancient Chinese medicine literature as more than 210 million words of research in this article, paragraph attribute analysis. And the use of TF (Term Frequency), IDF (Inverse Document Frequency), TF-IDF concept, analysis of ancient Chinese medicine text articles attribute definition paragraphs, and calculate the weight of keywords, the keywords, thereby building a knowledge base to calculated by means of keyword terms, the use of "data mining" (Data Mining) approach to ancient Chinese medicine is described in the article odor drug 【vapor】, 【meridian】, 【effect】 paragraphs capture the characteristics of field . In this study, combined with the knowledge of experts and scholars from the knowledge base integration, coupled with "data mining" (Data Mining) applications of information technology-assisted extraction keywords article attributes the characteristics of the paragraphs, and achieve the above purpose, the help of experts and scholars for the efficient reading of ancient Chinese medicine, Chinese medicine to enhance research