Research on Entity Relation Extraction in TCM Acupuncture and Moxibustion Field

For the context of entity relation instance in TCM acupuncture and moxibustion field, effective words, syntax and semantics features are chosen to combine into feature template, and the entity relation instances are vectorized. The classification models of entity relations in TCM acupuncture and moxibustion area are trained by the machine learning method which is based on support vector machine. The experimental results show that the feature template of entity relations in this thesis have excellent effects on the entity relation extraction in TCM acupuncture and moxibustion area. The F-measure of entity relation classification model of DM, HM, AM and DRM reached 93.25%, 87.19%, 86.57%and84.57% respectively.

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