A hidden Markov model-based text classification of medical documents

被引:22
|
作者
Yi, Kwan [1 ]
Beheshti, Jamshid [2 ]
机构
[1] Univ Kentucky, Sch Lib & Informat Sci, Little Fine Arts Lib 331, Lexington, KY 40506 USA
[2] McGill Univ, Sch Informat Studies, Montreal, PQ, Canada
关键词
hidden Markov model; HMM; MeSH; text classification; UMLS;
D O I
10.1177/0165551508092257
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The purpose of the study is to test the application of the hidden Markov model (HMM) using prior knowledge in medical text classification (TC). HMM has been applied to a wide range of applications in information processing, but not so much in TC applications. The Medical Subject Heading (MeSH) is utilized for prior knowledge in the model. A prototype for an HMM-based TC model is designed, and an experimental model based on the prototype is implemented so as to categorize medical documents into MeSH. A subset of OHSUMED is used for the experiments. Our results show that the performance of our model is comparable to those reported in the literature.
引用
收藏
页码:67 / 81
页数:15
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