Objective To explore the data mining method for establishing the core formulas and medicinal herbs for traditional Chinese medicine（TCM） doctors to give treatment based on syndrome differentiation. Methods By taking insomnia as an example

the data mining method was explored to analyze the clinical data in TCM practice. Based on the similarity of prescriptions

the target population was identified through classification models; the complex network of core formulas and medicinals

and the characteristics of people benefited from the prescription was constructed; subnetwork screening as well as a hierarchical core subnetwork mining algorithm were adopted to explore the core formulas and medicinals for insomnia patients who were benefited from the TCM treatment. Results Data from 101 insomnia patients involving 245 hospital visits were collected

among which 78 patients visited the hospital more than once. Sixty-eight patients（87.2%） showed effective result

while two as partially effective

and eight as non-effective. A complex network of clinical data of 78 patients（144 visits） were constructed for data mining. Target population was divided into two modules according to the similarity of prescriptions

and the module degree was 0.184. The core formula of module one was composed of Zhishi（Fructus Aurantii Immaturus）

Banxia（Rhizoma Pinelliae）

Qingmengshi（Lapis Chloriti）

Zhuru（Caulis Bambusae in Taenia）

Fuling（Poria）

Huanglian（Rhizoma Coptidis）

Juhong（Exocarpium Citri Rubrum）

Dahuang（Radix et Rhizoma Rhei）

Longchi（Dens Draconis）

and Zhenzhumu（Concha Margaritiferae Usta）; it was effective for patients who mainly had a red tongue

and yellow and greasy coating; had difficulty falling asleep; waked up early; and had many dreams; certain patients may present dry stool

dry mouth

bitter taste

uneasy feelings

dizziness

wiry and excess pulse. Conclusion The prescription similarity-based complex network data mining method can be used to initially reveal the characteristics of using drugs based on syndrome differentiation by TCM doctors

the result of which may further facilitate the data mining and inheritance of TCM famous doctors′ experience.