【知识图谱】知识图谱的构建-python-neo4j

概述环境依赖jdk、neo4j图数据库neo4j具体的安装过程可以参考这里：https://cloud.tencent.com/developer/article/1387732json数据{ "_id":{ "$oid":"5bb578b6831b973a137e3ee6" }, "name":"肺泡蛋白质沉积症", "desc":"肺泡蛋白质沉积症( 环境依赖

jdk、neo4j图数据库
neo4j具体的安装过程可以参考这里：https://cloud.tencent.com/developer/article/1387732

Json数据

{	"_ID": {		"$oID": "5bb578b6831b973a137e3ee6"	},	"name": "肺泡蛋白质沉积症",	"desc": "肺泡蛋白质沉积症(简称PAP)，又称Rosen-Castle-man-LIEbow综合征，是一种罕见疾病。该病以肺泡和细支气管腔内充满PAS染色阳性，来自肺的富磷脂蛋白质物质为其特征，好发于青中年，男性发病约3倍于女性。",	"category": ["疾病百科", "内科", "呼吸内科"],	"prevent": "1、避免感染分支杆菌病，卡氏肺囊肿肺炎，巨细胞病毒等。\n2、注意锻炼身体，提高免疫力。",	"cause": "病因未明，推测与几方面因素有关：如大量粉尘吸入（铝，二氧化硅等），机体免疫功能下降（尤其婴幼儿），遗传因素，酗酒，微生物感染等，而对于感染，有时很难确认是原发致病因素还是继发于肺泡蛋白沉着症，例如巨细胞病毒，卡氏肺孢子虫，组织胞浆菌感染等均发现有肺泡内高蛋白沉着。\n虽然启动因素尚不明确，但基本上同意发病过程为脂质代谢障碍所致，即由于机体内，外因素作用引起肺泡表面活性物质的代谢异常，到目前为止，研究较多的有肺泡巨噬细胞活力，动物实验证明巨噬细胞吞噬粉尘后其活力明显下降，而病员灌洗液中的巨噬细胞内颗粒可使正常细胞活力下降，经支气管肺泡灌洗治疗后，其肺泡巨噬细胞活力可上升，而研究未发现Ⅱ型细胞生成蛋白增加，全身脂代谢也无异常，因此目前一般认为本病与清除能力下降有关。",	"symptom": ["紫绀", "胸痛", "呼吸困难", "乏力", "毓卓"],	"yibao_status": "否",	"get_prob": "0.00002%",	"get_way": "无传染性",	"acompany": ["多重肺部感染"],	"cure_department": ["内科", "呼吸内科"],	"cure_way": ["支气管肺泡灌洗"],	"cure_lasttime": "约3个月",	"cured_prob": "约40%",	"cost_money": "根据不同医院，收费标准不一致，省市三甲医院约（ 8000——15000 元）",	"check": ["胸部CT检查", "肺活检", "支气管镜检查"],	"recommand_drug": [],	"drug_detail": []} ......

实例

import osimport Jsonfrom py2neo import Graph, Nodeclass MedicalGraph:    def __init__(self):        cur_dir = '\'.join(os.path.abspath(__file__).split('\')[:-1])        self.data_path = os.path.join(cur_dir, 'data\medical2.Json')        self.g = Graph("http://localhost:7474", username="neo4j", password="rhino1qaz@wsx")    def read_nodes(self):        diseases = []  # 疾病        drugs = []  # 药品        departments = []  # 科室        disease_infos = []        rels_disease_drug = [] #疾病和药品之间的关系        rels_disease_department = [] #疾病和科室之间的关系        rels_department_department = [] #科室和科室之间的关系        count = 0        for data in open(self.data_path):            disease_dict = {}            count += 1            print(count)            # 读取每一行数据            data_Json = Json.loads(data)            print(data_Json)            disease = data_Json['name']            disease_dict['name'] = disease  # 疾病名            diseases.append(disease)            if 'cure_department' in data_Json:                cure_department = data_Json['cure_department']                if len(cure_department) == 1:                    rels_disease_department.append([disease, cure_department[0]])                if len(cure_department) == 2:                    big = cure_department[0]                    small = cure_department[1]                    rels_department_department.append([small, big])                    rels_disease_department.append([disease, small])                disease_dict['cure_department'] = cure_department                departments += cure_department            if 'recommand_drug' in data_Json:                recommand_drug = data_Json['recommand_drug']                drugs += recommand_drug                for drug in recommand_drug:                    rels_disease_drug.append([disease, drug])                disease_dict['recommand_drug'] = recommand_drug            disease_infos.append(disease_dict)        return set(diseases), set(drugs), set(departments), disease_infos, \               rels_disease_drug, rels_disease_department, rels_department_department    def create_node(self, label, nodes):        count = 0        for node_name in nodes:            node = Node(label, name=node_name)            self.g.create(node)            count += 1            print(count, len(nodes))        return    '''创建知识图谱中心疾病的节点'''    def create_diseases_nodes(self, disease_infos):        count = 0        for disease_dict in disease_infos:            node = Node("disease", name=disease_dict['name'], recommand_drug=disease_dict['recommand_drug'],                        cure_department=disease_dict['cure_department'])            self.g.create(node)            count += 1            print(count)        return    '''创建知识图谱实体节点类型schema'''    def create_graphnodes(self):        diseases, Drugs, Departments, disease_infos, \        rels_disease_drug, rels_disease_department, rels_department_department = self.read_nodes()        self.create_diseases_nodes(disease_infos)        self.create_node('Drug', Drugs)        print(len(Drugs))        self.create_node('Department', Departments)        print(len(Departments))        return    '''创建实体关系边'''    def create_graphrels(self):        diseases, Drugs, Departments, disease_infos, \        rels_disease_drug, rels_disease_department, rels_department_department = self.read_nodes()        self.create_relationship('disease', 'Drug', rels_disease_drug, 'recommand_eat', '宜吃')        self.create_relationship('disease', 'Department', rels_disease_department, 'belongs_to', '所属科室')        self.create_relationship('Department', 'Department', rels_department_department, 'belongs_to', '属于')    def create_relationship(self, start_node, end_node, edges, rel_type, rel_name):        count = 0        # 去重处理        set_edges = []        for edge in edges:            set_edges.append('###'.join(edge))        all = len(set(set_edges))        for edge in set(set_edges):            edge = edge.split('###')            p = edge[0]            q = edge[1]            query = "match(p:%s),(q:%s) where p.name='%s'and q.name='%s' create (p)-[rel:%s{name:'%s'}]->(q)" % (                start_node, end_node, p, q, rel_type, rel_name)            try:                self.g.run(query)                count += 1                print(rel_type, count, all)            except Exception as e:                print(e)        return    '''导出数据'''    def export_data(self):        diseases, Drugs, Departments, disease_infos, \        rels_disease_drug, rels_disease_department, rels_department_department = self.read_nodes()        f_disease = open('disease.txt', 'w+')        f_drug = open('drug.txt', 'w+')        f_department = open('department.txt', 'w+')        f_disease.write('\n'.join(List(diseases)))        f_drug.write('\n'.join(List(Drugs)))        f_department.write('\n'.join(List(Departments)))        f_disease.close()        f_drug.close()        f_department.close()        returnif __name__ == '__main__':    medicalGraph = MedicalGraph()    medicalGraph.create_graphnodes()    medicalGraph.create_graphrels()    medicalGraph.export_data()

无非就是连接图数据库，然后创建节点、创建关系，当做模板来看就行了，最后结果：

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