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학술저널

의료 웹포럼에서의 텍스트 분석을 통한 정보적 지지 및 감성적 지지 유형의 글 분류 모델

The Informative Support and Emotional Support Classification Model for Medical Web Forums using Text Analysis

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In the medical web forum, people share medical experience and information as patients and patents’ families. Some people search medical information written in non-expert language and some people offer words of comport to who are suffering from diseases. Medical web forums play a role of the informative support and the emotional support. We propose the automatic classification model of articles in the medical web forum into the information support and emotional support. We extract text features of articles in web forum using text mining techniques from the perspective of linguistics and then perform supervised learning to classify texts into the information support and the emotional support types. We adopt the Support Vector Machine (SVM), Naive-Bayesian, decision tree for automatic classification. We apply the proposed mode to the HealthBoards forum, which is also one of the largest and most dynamic medical web forum.

Abstract

1. 서론

2. 문헌 연구

3. 연구방법

4. 의료 웹포럼에의 적용

5. 결론 및 향후 연구방안

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