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Entity Recognition Research in Online Medical Texts
SU Ya, LIU Jie, HUANG Yalou
Acta Scientiarum Naturalium Universitatis Pekinensis    2016, 52 (1): 1-9.   DOI: 10.13209/j.0479-8023.2016.020
Abstract1508)   HTML    PDF(pc) (1120KB)(1860)       Save

The authors design recognition features with the consideration of medical field characteristic for the online medical text, and the experiment of the entity recognition is carried out on the self-built data set. Concerned about five common diseases: gastritis, lung cancer, asthma, hypertension and diabetes. In the experiment, an advanced machine learning model Conditional Random Field is used for training and testing. The target entities include five kinds: disease, symptoms, drugs, treatment methods and check. The effectiveness of the proposed features is verified by using the experimental method, and the accuracy of the total 81.26% is obtained and the recall rate is 60.18%. Subsequently, the further analysis is given for the recognition features.

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