数字中医药（英文）2019，Vol.2Issue(2)：61-71,11.DOI:10.1016/j.dcmed.2019.09.001
运用自然语言处理对证素辨证学进行文本挖掘研究
Research on Text Mining of Syndrome Element Syndrome Differentiation by Natural Language Processing
摘要
Abstract
Objective Natural language processing (NLP) was used to excavate and visualize the core content of syndrome element syndrome differentiation (SESD). Methods The first step was to build a text mining and analysis environment based on Python language, and built a corpus based on the core chapters of SESD. The second step was to digitalize the corpus. The main steps included word segmentation, information cleaning and merging, document-entry matrix, dictionary compilation and information conversion. The third step was to mine and display the internal information of SESD corpus by means of word cloud, keyword extraction and visualization. Results NLP played a positive role in computer recognition and comprehension of SESD. Different chapters had different keywords and weights. Deficiency syndrome elements were an important component of SESD, such as "Qi deficiency" "Yang deficiency" and "Yin deficiency". The important syndrome elements of substantiality included "Blood stasis" "Qi stagnation", etc. Core syndrome elements were closely related. Conclusions Syndrome differentiation and treatment was the core of SESD. Using NLP to excavate syndromes differentiation could help reveal the internal relationship between syndromes differentiation and provide basis for artificial intelligence to learn syndromes differentiation.关键词
证素辨证学/自然语言处理/中医诊断学/人工智能/文本挖掘Key words
Syndrome element syndrome differentiation (SESD)/Natural language processing (NLP)/Diagnostics of TCM/Artificial intelligence/Text mining引用本文复制引用
邓文祥,朱建平,李静,袁志鹰,吴华英,姚中华,张弋戈,张文安,黄惠勇..运用自然语言处理对证素辨证学进行文本挖掘研究[J].数字中医药（英文）,2019,2(2):61-71,11.基金项目
We thank for the funding support from the National Natural Science Foundation of China (No. 81874429), Digital and Applied Research Platform for Diagnosis of Traditional Chinese Medicine (No. 49021003005), 2018 Hunan Provincial Postgraduate Research Innovation Project (No. CX2018B465) and Excellent Youth Project of Hunan Education Department in 2018 (No. 18B241). （No. 81874429）
