A Multigranularity Text Driven Named Entity Recognition CGAN Model for Traditional Chinese Medicine Literatures

<table class="table-group" id="tab1"><tr><td><table class="table"><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr class="thead"><td class="align_left">Type of literature</td><td class="align_center">Typical entity types and corresponding labels</td></tr><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left">Canon of medicine</td><td class="align_center">Cognitive method (RSFF), traditional Chinese physiology (ZYSL), traditional Chinese pathology (ZYBL), the principle of treatment (ZZ), method of treatment (ZF)</td></tr><tr><td class="align_left">Medical cases</td><td class="align_center">Chinese materia medica (ZY), symptoms (ZZ), pulse (MX), tongue (SX), formula (FJ), dosis (FJ)</td></tr><tr><td class="align_left">Herbal</td><td class="align_center">Drug property (YX), flavor of medicinals (YW), channel tropism (GJ), virtue (GX), dilantin (YM), symptoms (ZZ)</td></tr><tr><td class="align_left">Comprehensive</td><td class="align_center">Pathogeny (BY), disease (JB), syndrome (ZH), pulse (MX), tongue (SX), formula (FJ), Chinese materiamedica (ZY)</td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Typical types of entities contained in different types of TCM texts.</div>

Computational Intelligence and Neuroscience

tab1

Table 1

Table 1: A Multigranularity Text Driven Named Entity Recognition CGAN Model for Traditional Chinese Medicine Literatures 