Paper: A Preliminary Work on Symptom Name Recognition from Free-Text Clinical Records of Traditional Chinese Medicine using Conditional Random Fields and Reasonable Features

ACL ID W12-2428
Title A Preliminary Work on Symptom Name Recognition from Free-Text Clinical Records of Traditional Chinese Medicine using Conditional Random Fields and Reasonable Features
Venue Workshop on Biomedical Natural Language Processing
Session
Year 2012
Authors

A preliminary work on symptom name recog- nition from free-text clinical records (FCRs) of traditional Chinese medicine (TCM) is de- picted in this paper. This problem is viewed as labeling each character in FCRs of TCM with a pre-defined tag (?B-SYC?, ?I-SYC? or ?O- SYC?) to indicate the character?s role (a be- ginning, inside or outside part of a symptom name). The task is handled by Conditional Random Fields (CRFs) based on two types of features. The symptom name recognition F- Measure can reach up to 62.829% with recog- nition rate 93.403% and recognition error rate 52.665% under our experiment settings. The feasibility and effectiveness of the methods and reasonable features are verified, and sev- eral interesting and helpful results are shown. A detailed analysis for recogn...