A Study on Classification of Medical Information Documents using Word Correlation


The KIPS Transactions:PartB , Vol. 8, No. 5, pp. 469-476, Oct. 2001
10.3745/KIPSTB.2001.8.5.469,   PDF Download:

Abstract

As the service of information through web system increases in modern society, many questions and consultations are going on through Home page and E-mail in the hospital. But there are some burdens for the management and postponements for answering the questions. In this paper, we investigate the document classification methods as a primary research of the auto-answering system. On the basis of 1200 documents which are questions of patients, 66% are used for the learning documents and 34% for test documents. All of these are also used for the document classification using NBC (Naive Bayes Classifier), common words and coefficient of correlation. As the result of the experiments, the two methods proposed in this paper, that is, common words and coefficient of correlation are higher as much as 3% and 5% respectively than the basic NBC methods. This result shows that the correlation between indexes and categories is more effective than the word frequency in the document classification.


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Cite this article
[IEEE Style]
H. G. Lim and D. S. Jang, "A Study on Classification of Medical Information Documents using Word Correlation," The KIPS Transactions:PartB , vol. 8, no. 5, pp. 469-476, 2001. DOI: 10.3745/KIPSTB.2001.8.5.469.

[ACM Style]
Hyeong Geon Lim and Duk Sung Jang. 2001. A Study on Classification of Medical Information Documents using Word Correlation. The KIPS Transactions:PartB , 8, 5, (2001), 469-476. DOI: 10.3745/KIPSTB.2001.8.5.469.