A hidden Markov model-based text classification of medical documents

  • Authors:
  • Kwan Yi;Jamshid Beheshti

  • Affiliations:
  • School of Library and Information Science, Universityof Kentucky, USA;School of Information Studies, McGill University, Montreal,Canada

  • Venue:
  • Journal of Information Science
  • Year:
  • 2009

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Abstract

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.