Force

├── Protege使用 ├── KGexample.owl ├── Protege-5.0.0-beta-16.zip ├── catalog-v001.xml ├── readme.txt ├── 效果.PNG └── 第二讲知识表示和知识建模 (1).pdf ├── README.md ├── 常用开放知识图谱API调用 ├── CN_DBpedia.py ├── __init__.py ├── readme.txt └── wikipedia.py ├── 汽车行业知识图谱第一次验收 ├── conf.py ├── data │ ├── __init__.py │ ├── data.py │ ├── mysql.py │ └── three_tuples.txt ├── readme.txt ├── visualization │ ├── .DS_Store │ ├── __init__.py │ ├── run_server.py │ └── server │ │ ├── .DS_Store │ │ ├── __init__.py │ │ ├── app.py │ │ ├── models.py │ │ ├── mysql.py │ │ ├── templates │ │ ├── .DS_Store │ │ ├── d3.zip │ │ ├── data.json │ │ └── index.html │ │ └── views.py └── 效果.PNG ├── 汽车行业知识图谱第二次验收 ├── __init__.py ├── conf.py ├── data │ ├── http接口说明.txt │ ├── statistics.txt │ └── three_tuples.txt ├── kg │ ├── kg.py │ └── kg_test.py ├── readme.txt ├── server │ ├── .DS_Store │ ├── __init__.py │ ├── app.py │ ├── http_test.py │ ├── module.py │ ├── run_server.py │ └── views.py ├── test.py └── 效果.png └── 知识图谱学习笔记 └── 笔记.docx /Protege使用/KGexample.owl: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 6 | 7 | 8 | 9 | 10 | ]> 11 | 12 | 13 | 20 | 21 | 22 | 23 | 24 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 | 58 | 59 | 60 | 61 | 62 | 63 | 64 | 65 | 66 | 67 | 68 | 69 | 70 | 71 | 72 | 73 | 74 | 75 | 76 | 77 | 78 | 79 | 86 | 87 | 88 | 89 | 90 | 91 | 92 | 93 | 94 | 95 | 96 | 97 | 98 | 99 | 100 | 101 | 102 | 103 | 104 | 105 | 112 | 113 | 114 | 115 | 116 | 117 | 118 | 119 | 120 | 121 | 122 | 123 | 124 | 125 | 126 | 127 | 128 | 129 | 130 | 131 | 132 | 133 | 134 | 135 | 136 | 137 | 138 | 139 | 140 | 141 | 142 | 143 | 144 | 145 | 146 | 147 | 148 | 149 | 150 | 151 | 152 | 153 | 154 | 155 | 156 | 157 | 158 | 159 | 160 | 161 | 162 | 163 | 170 | 171 | 172 | 173 | 174 | 175 | 176 | 177 | 178 | <曾住 rdf:resource="&untitled-ontology-6;镇江金山寺"/> 179 | 180 | 181 | 182 | 183 | 184 | 185 | 186 | 187 | 188 | 189 | 190 | 191 | 192 | 193 | 194 | 195 | <别名>苏东坡、东坡 196 | <相识 rdf:resource="&untitled-ontology-6;佛印禅师"/> 197 | 198 | 199 | 200 | 201 | 202 | 203 | 204 | 205 | <法号>法海 206 | 207 | 208 | 209 | 210 | 211 | 212 | 213 | 214 | 215 | 216 | 217 | 218 | 219 | 220 | 221 | -------------------------------------------------------------------------------- /Protege使用/Protege-5.0.0-beta-16.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/qiu997018209/KnowledgeGraph/5d91826c2346b9f9f301f99278e98464d79fbb4b/Protege使用/Protege-5.0.0-beta-16.zip -------------------------------------------------------------------------------- /Protege使用/catalog-v001.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | -------------------------------------------------------------------------------- /Protege使用/readme.txt: -------------------------------------------------------------------------------- 1 | 1.使用介绍:第二讲知识表示和知识建模 (1).pdf 2 | 3 | 2.安装程序:Protege-5.0.0-beta-16.zip 4 | 5 | 3.示例程序:KGexample.owl 6 | 7 | 4.效果:效果.PNG 8 | 9 | 5.作用:本体建模 -------------------------------------------------------------------------------- /Protege使用/效果.PNG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/qiu997018209/KnowledgeGraph/5d91826c2346b9f9f301f99278e98464d79fbb4b/Protege使用/效果.PNG -------------------------------------------------------------------------------- /Protege使用/第二讲知识表示和知识建模 (1).pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/qiu997018209/KnowledgeGraph/5d91826c2346b9f9f301f99278e98464d79fbb4b/Protege使用/第二讲知识表示和知识建模 (1).pdf -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # KnowledgeGraph 2 | 知识图谱车音工作项目 3 | -------------------------------------------------------------------------------- /常用开放知识图谱API调用/CN_DBpedia.py: -------------------------------------------------------------------------------- 1 | #coding:utf-8 2 | ''' 3 | Created on 2018年1月12日 4 | 5 | @author: qiujiahao 6 | 7 | @email:997018209@qq.com 8 | 9 | ''' 10 | 11 | 12 | 13 | import json 14 | import requests 15 | 16 | #查询实体 17 | url='http://shuyantech.com/api/cndbpedia/avpair' 18 | quest={'q':'复旦大学'} 19 | print(requests.post(url,quest).text) 20 | 21 | #查询概念 22 | url='http://shuyantech.com/api/cnprobase/concept' 23 | quest={'q':'刘德华'} 24 | print(requests.post(url,quest).text) -------------------------------------------------------------------------------- /常用开放知识图谱API调用/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/qiu997018209/KnowledgeGraph/5d91826c2346b9f9f301f99278e98464d79fbb4b/常用开放知识图谱API调用/__init__.py -------------------------------------------------------------------------------- /常用开放知识图谱API调用/readme.txt: -------------------------------------------------------------------------------- 1 | 1.google的api可以返回不同实体的得分，只能读,需要翻墙 2 | 3 | 2.wikipedia可以返回网页信息，例如标题，概要，其它不可,可编辑,需要翻墙 4 | 5 | 3.CN_DBpedia可以中文查询概念的知识图谱，并返回相应概念的权重，不需要翻墙 -------------------------------------------------------------------------------- /常用开放知识图谱API调用/wikipedia.py: -------------------------------------------------------------------------------- 1 | #coding:utf-8 2 | ''' 3 | Created on 2018年1月12日 4 | 5 | @author: qiujiahao 6 | 7 | @email:997018209@qq.com 8 | 9 | 介绍:https://github.com/goldsmith/Wikipedia 10 | ''' 11 | import wikipedia 12 | 13 | def show(data): 14 | try: 15 | print('title',data.title)#标题 16 | print('title',data.url)#页面url 17 | print('title',data.content)#页面内容 18 | print('title',data.links[0])#页面连接 19 | except: 20 | print(data) 21 | 22 | wikipedia.set_lang('zh')#设置语言 23 | print(wikipedia.search('中山大小'))#搜索 24 | my=wikipedia.page('中山大小')#获取页面 25 | show(my) 26 | -------------------------------------------------------------------------------- /汽车行业知识图谱第一次验收/conf.py: -------------------------------------------------------------------------------- 1 | #coding:utf-8 2 | ''' 3 | Created on 2017年12月11日 4 | 5 | @author: qiujiahao 6 | 7 | @email:997018209@qq.com 8 | 9 | ''' 10 | #数据路径 11 | DATA_PATH='data/web' 12 | 13 | #MYSQL信息 14 | MYSQL_HOST="192.168.1.245" 15 | MYSQL_PORT=3306 16 | MYSQL_USER="knowInfo" 17 | MYSQL_PASSWORD="knowInfo" 18 | MYSQL_db='KnowGrah_car_info' 19 | 20 | #web 21 | http_host='0.0.0.0' 22 | http_port=8090 23 | #json_path="/templates/data.json" 24 | json_path="/server/templates/data.json" 25 | 26 | -------------------------------------------------------------------------------- /汽车行业知识图谱第一次验收/data/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/qiu997018209/KnowledgeGraph/5d91826c2346b9f9f301f99278e98464d79fbb4b/汽车行业知识图谱第一次验收/data/__init__.py -------------------------------------------------------------------------------- /汽车行业知识图谱第一次验收/data/data.py: -------------------------------------------------------------------------------- 1 | #coding:utf-8 2 | ''' 3 | Created on 2017年11月27日 4 | 5 | @author: qiujiahao 6 | 7 | @email:997018209@qq.com 8 | 9 | ''' 10 | import os 11 | import re 12 | import sys 13 | sys.path.append("..") 14 | from conf import * 15 | from bs4 import BeautifulSoup 16 | 17 | class data(object): 18 | def __init__(self): 19 | #self.database=database() 20 | self.process_cars() 21 | def process_cars(self): 22 | #连接数据库 23 | f= open(os.path.join(DATA_PATH,'..','three_tuples.txt'),'w',encoding='utf-8') 24 | for _,_,files in os.walk(DATA_PATH): 25 | for file in files: 26 | print('进度:%s:%d/%d'%(file,files.index(file)+1,len(files))) 27 | my_data=self.process_html(file) 28 | if(my_data==None): 29 | continue 30 | for data in my_data: 31 | f.write('%s:%s:%s\n'%(data[0],data[1],data[2])) 32 | 33 | #self.database.execute(car_info) 34 | #解析每一个html 35 | def process_html(self,file): 36 | file = open(os.path.join(DATA_PATH,file),'r',encoding='utf-8') 37 | my_data=set() 38 | soup=BeautifulSoup(file,'html.parser', from_encoding='utf-8') 39 | 40 | main_key=soup.find('title') 41 | if main_key==None: 42 | return None 43 | main_key=self.clean_string(main_key.string) 44 | names=[] 45 | for value in soup.find_all('dt',class_='basicInfo-item name'): 46 | names.append(self.clean_string(value.string)) 47 | values=[] 48 | for value in soup.find_all('dd',class_='basicInfo-item value'): 49 | if value.string==None: 50 | values.append(self.clean_string(value.get_text())) 51 | else: 52 | values.append(self.clean_string(value.string)) 53 | if(len(values)!=len(names)): 54 | my_data=[] 55 | return 56 | for name in names: 57 | value=values[names.index(name)] 58 | my_data.add((main_key,name,value)) 59 | #print(my_data[0]) 60 | return my_data 61 | 62 | def clean_string(self,value): 63 | if(value=='' or value==None): 64 | return 65 | value=value.strip().replace(' ','').upper() 66 | value = re.compile(r"_百度百科").sub('',value) 67 | value = re.compile(r"\[.*\]").sub('',value) 68 | value = re.compile(r"\(.*\)").sub('',value) 69 | value = re.compile(r"\（.*\）").sub('',value) 70 | value = re.compile(r" ").sub('',value) 71 | return value 72 | 73 | if __name__ == "__main__": 74 | data=data() 75 | 76 | 77 | 78 | 79 | 80 | 81 | 82 | 83 | 84 | 85 | 86 | 87 | -------------------------------------------------------------------------------- /汽车行业知识图谱第一次验收/data/mysql.py: -------------------------------------------------------------------------------- 1 | #coding:utf-8 2 | ''' 3 | Created on 2017年12月11日 4 | 5 | @author: qiujiahao 6 | 7 | @email:997018209@qq.com 8 | 9 | ''' 10 | import pymysql 11 | import os 12 | import sys 13 | sys.path.append("..") 14 | from conf import * 15 | 16 | car_node=''' 17 | create table car_node( 18 | id int primary key NOT NULL AUTO_INCREMENT, 19 | name varchar(100), 20 | ext varchar(500), 21 | create_time DATETIME, 22 | create_id INT(32), 23 | update_time DATETIME, 24 | update_id INT(32), 25 | is_delete INT DEFAULT '0' NOT NULL 26 | ); 27 | ''' 28 | car_node_attribute=''' 29 | create table car_node_attribute( 30 | id int primary key NOT NULL AUTO_INCREMENT, 31 | node_id int not null, 32 | attribute_name varchar(200), 33 | attribute_value varchar(200), 34 | is_delete INT DEFAULT '0' NOT NULL 35 | ); 36 | ''' 37 | class database(object): 38 | def __init__(self): 39 | self.conn = pymysql.connect( 40 | host = MYSQL_HOST, 41 | port = MYSQL_PORT, 42 | user = MYSQL_USER, 43 | password = MYSQL_PASSWORD, 44 | charset ='utf8', 45 | db = MYSQL_db) 46 | self.cursor = self.conn.cursor() 47 | def __del__(self): 48 | self.conn.close() 49 | def data_process(self): 50 | with open(os.path.join(DATA_PATH,'..','three_tuples.txt'),'r',encoding='utf-8') as f: 51 | for line in f.readlines(): 52 | line=self.clean_string(line).split(':') 53 | if len(line)!=3: 54 | continue 55 | mysql_cmd="select id from car_node where name='%s';"%(line[0]) 56 | count=self.cursor.execute(mysql_cmd) 57 | if(count==0): 58 | mysql_cmd="insert into car_node(name) values('%s');"%(line[0]) 59 | self.cursor.execute(mysql_cmd) 60 | node_id=self.conn.insert_id() 61 | #print(node_id,line[1],line[2]) 62 | mysql_cmd='''insert into car_node_attribute(node_id,attribute_name,attribute_value) values(%d,'%s','%s');'''%(node_id,line[1],line[2]) 63 | self.cursor.execute(mysql_cmd) 64 | else: 65 | result=self.cursor.fetchone() 66 | node_id=result[0] 67 | mysql_cmd='''insert into car_node_attribute 68 | (node_id,attribute_name,attribute_value) values(%d,'%s','%s');'''%(node_id,line[1],line[2]) 69 | print(mysql_cmd) 70 | self.cursor.execute(mysql_cmd) 71 | self.conn.commit() 72 | 73 | def clean_string(self,value): 74 | if(value=='' or value==None): 75 | return 76 | value=value.strip().replace('\'','') 77 | return value 78 | 79 | if __name__=='__main__': 80 | database=database() 81 | database.data_process() 82 | 83 | -------------------------------------------------------------------------------- /汽车行业知识图谱第一次验收/readme.txt: -------------------------------------------------------------------------------- 1 | 环境:python3+flask+mysql+D3 2 | 3 | 1.data:数据处理 4 | (1)data.py将爬虫趴下来的html数据处理成三元组，存在文件:three_tuples.txt 5 | (2)mysql.py将three_tuples.txt里数据存入Mysql数据 6 | 7 | 2.visualization:可视化 8 | (1)执行run_server.py，启动web服务，然后在浏览器中输入: 9 | http://192.168.1.245:8090/api/v1?car_name=日产天籁 10 | (2)原理:flask框架下查询mysql，存入json文件，index.html导入json文件，采用用D3的js框架 11 | (3)效果见:效果.PNG 12 | (4)数据量:11200个 13 | 3.conf.py:配置文件 -------------------------------------------------------------------------------- /汽车行业知识图谱第一次验收/visualization/.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/qiu997018209/KnowledgeGraph/5d91826c2346b9f9f301f99278e98464d79fbb4b/汽车行业知识图谱第一次验收/visualization/.DS_Store -------------------------------------------------------------------------------- /汽车行业知识图谱第一次验收/visualization/__init__.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | 3 | 4 | -------------------------------------------------------------------------------- /汽车行业知识图谱第一次验收/visualization/run_server.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | # @Author: ioriiod0 3 | # @Date: 2017-07-12 11:47:28 4 | # @Last Modified by: ioriiod0 5 | # @Last Modified time: 2017-07-14 19:21:37 6 | import sys 7 | sys.path.append("..") 8 | 9 | import gevent 10 | from gevent.monkey import patch_all 11 | from conf import * 12 | ''' 13 | gevent是第三方库，通过greenlet实现协程，其基本思想是： 14 | 当一个greenlet遇到IO操作时，比如访问网络，就自动切换到其他的greenlet，等到IO操作完成，再在适当的时候切换回来继续执行。 15 | 由于IO操作非常耗时，经常使程序处于等待状态，有了gevent为我们自动切换协程，就保证总有greenlet在运行，而不是等待IO。 16 | 由于切换是在IO操作时自动完成，所以gevent需要修改Python自带的一些标准库，这一过程在启动时通过monkey patch完成： 17 | ''' 18 | patch_all() 19 | from server.app import app 20 | 21 | if __name__ == '__main__': 22 | app.run(debug=True, host=http_host, port=http_port) 23 | -------------------------------------------------------------------------------- /汽车行业知识图谱第一次验收/visualization/server/.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/qiu997018209/KnowledgeGraph/5d91826c2346b9f9f301f99278e98464d79fbb4b/汽车行业知识图谱第一次验收/visualization/server/.DS_Store -------------------------------------------------------------------------------- /汽车行业知识图谱第一次验收/visualization/server/__init__.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | 3 | 4 | -------------------------------------------------------------------------------- /汽车行业知识图谱第一次验收/visualization/server/app.py: -------------------------------------------------------------------------------- 1 | from flask import Flask 2 | 3 | app = Flask(__name__) 4 | 5 | from server.views import * 6 | -------------------------------------------------------------------------------- /汽车行业知识图谱第一次验收/visualization/server/models.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | # @Author: Shuang0420 3 | # @Date: 2017-08-29 17:08:03 4 | # @Last Modified by: Shuang0420 5 | # @Last Modified time: 2017-08-29 18:58:13 6 | 7 | 8 | import json 9 | import json 10 | import pymysql 11 | import sys 12 | import os 13 | from conf import * 14 | 15 | fname = os.getcwd() + json_path 16 | 17 | edge_sql_car = """select a.attribute_name,a.attribute_value from car_node n,car_node_attribute a where n.id = a.node_id and n.name = '%s';""" 18 | edge_sql_relation = """SELECT subj, obj, pred, company.company_name, company.code, person.name, type FROM spo JOIN company JOIN person WHERE spo.subj=company.id AND spo.obj=person.id AND person.name="%s";""" 19 | secondary_edge_sql = 'SELECT * FROM spo WHERE subj="%s"' 20 | 21 | def execute(database, attr): 22 | js = {} 23 | edges=[] 24 | try: 25 | if attr[0]=='car_name': 26 | sql = edge_sql_car%(attr[1]) 27 | count=database.cursor.execute(sql) 28 | if count != 0: 29 | for result in database.cursor.fetchall(): 30 | print(result) 31 | edges.append({"source": attr[1], "target": result[1], "relation": result[0], "label": 'relation'}) 32 | else: 33 | print('car_name不存在') 34 | except: 35 | print("ERROR: " + sql) 36 | database.conn.rollback() 37 | # js["nodes"] = nodes 38 | js["edges"] = edges 39 | mydata = json.dumps(js, ensure_ascii=False).encode("utf8") 40 | print('Json路径是:%s'%(fname)) 41 | with open(fname, 'w',encoding='utf-8') as f: 42 | f.write(str(mydata)) 43 | return mydata 44 | -------------------------------------------------------------------------------- /汽车行业知识图谱第一次验收/visualization/server/mysql.py: -------------------------------------------------------------------------------- 1 | #coding:utf-8 2 | ''' 3 | Created on 2017年12月11日 4 | 5 | @author: qiujiahao 6 | 7 | @email:997018209@qq.com 8 | 9 | ''' 10 | import pymysql 11 | import os 12 | from conf import * 13 | 14 | class database(object): 15 | def __init__(self): 16 | self.conn = pymysql.connect( 17 | host = MYSQL_HOST, 18 | port = MYSQL_PORT, 19 | user = MYSQL_USER, 20 | password = MYSQL_PASSWORD, 21 | charset ='utf8', 22 | db = MYSQL_db) 23 | self.cursor = self.conn.cursor() 24 | def __del__(self): 25 | self.conn.close() 26 | 27 | 28 | if __name__=='__main__': 29 | database=database() -------------------------------------------------------------------------------- /汽车行业知识图谱第一次验收/visualization/server/templates/.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/qiu997018209/KnowledgeGraph/5d91826c2346b9f9f301f99278e98464d79fbb4b/汽车行业知识图谱第一次验收/visualization/server/templates/.DS_Store -------------------------------------------------------------------------------- /汽车行业知识图谱第一次验收/visualization/server/templates/d3.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/qiu997018209/KnowledgeGraph/5d91826c2346b9f9f301f99278e98464d79fbb4b/汽车行业知识图谱第一次验收/visualization/server/templates/d3.zip -------------------------------------------------------------------------------- /汽车行业知识图谱第一次验收/visualization/server/templates/data.json: -------------------------------------------------------------------------------- 1 | b'{"edges": [{"source": "\xe6\x97\xa5\xe4\xba\xa7\xe5\xa4\xa9\xe7\xb1\x81", "relation": "\xe7\x94\x9f\xe4\xba\xa7\xe5\x8e\x82\xe5\x95\x86", "target": 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"relation"}, {"source": "\xe6\x97\xa5\xe4\xba\xa7\xe5\xa4\xa9\xe7\xb1\x81", "relation": "\xe8\xbd\xb4\xe8\xb7\x9d", "target": "2775\xe6\xaf\xab\xe7\xb1\xb3", "label": "relation"}, {"source": "\xe6\x97\xa5\xe4\xba\xa7\xe5\xa4\xa9\xe7\xb1\x81", "relation": "\xe8\xbd\xa6\xe5\x9e\x8b\xe5\xb0\xba\xe5\xaf\xb8", "target": "4.868\xe7\xb1\xb31.830\xe7\xb1\xb31.490\xe7\xb1\xb3", "label": "relation"}, {"source": "\xe6\x97\xa5\xe4\xba\xa7\xe5\xa4\xa9\xe7\xb1\x81", "relation": "\xe6\xb2\xb9\xe8\x80\x97", "target": "7.3\xe5\x8d\x87/\xe7\x99\xbe\xe5\x85\xac\xe9\x87\x8c", "label": "relation"}, {"source": "\xe6\x97\xa5\xe4\xba\xa7\xe5\xa4\xa9\xe7\xb1\x81", "relation": "\xe6\xb2\xb9\xe7\xae\xb1\xe5\xae\xb9\xe7\xa7\xaf", "target": "70L", "label": "relation"}, {"source": "\xe6\x97\xa5\xe4\xba\xa7\xe5\xa4\xa9\xe7\xb1\x81", "relation": "\xe5\x88\xb6\xe5\x8a\xa8\xe6\x96\xb9\xe5\xbc\x8f", "target": "\xe9\x80\x9a\xe9\xa3\x8e\xe7\x9b\x98\xe5\xbc\x8f", "label": "relation"}, {"source": "\xe6\x97\xa5\xe4\xba\xa7\xe5\xa4\xa9\xe7\xb1\x81", "relation": "\xe5\xbc\x95\xe6\x93\x8e\xe7\xb1\xbb\xe5\x9e\x8b", "target": "\xe7\x9b\xb4\xe5\x88\x974\xe7\xbc\xb8/\xe5\x8f\x8c\xe9\xa1\xb6\xe7\xbd\xae\xe5\x87\xb8\xe8\xbd\xae\xe8\xbd\xb4", "label": "relation"}, {"source": "\xe6\x97\xa5\xe4\xba\xa7\xe5\xa4\xa9\xe7\xb1\x81", "relation": "\xe6\x9c\x80\xe9\xab\x98\xe6\x97\xb6\xe9\x80\x9f", "target": "210KM/H", "label": "relation"}, {"source": "\xe6\x97\xa5\xe4\xba\xa7\xe5\xa4\xa9\xe7\xb1\x81", "relation": "\xe8\xa1\x8c\xe6\x9d\x8e\xe8\x88\xb1\xe5\xae\xb9\xe7\xa7\xaf", "target": "516L", "label": "relation"}, {"source": "\xe6\x97\xa5\xe4\xba\xa7\xe5\xa4\xa9\xe7\xb1\x81", "relation": "\xe6\x9c\x80\xe5\xa4\xa7\xe5\x8a\x9f\xe7\x8e\x87", "target": "137KW/RPM", "label": "relation"}]}' -------------------------------------------------------------------------------- /汽车行业知识图谱第一次验收/visualization/server/templates/index.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | Force 5 | 75 | 76 | 77 | 298 | 299 | 300 | -------------------------------------------------------------------------------- /汽车行业知识图谱第一次验收/visualization/server/views.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | # @Author: ioriiod0 3 | # @Date: 2017-07-12 13:24:54 4 | # @Last Modified by: ioriiod0 5 | # @Last Modified time: 2017-07-13 23:57:12 6 | 7 | import os 8 | import time 9 | 10 | from flask import request,render_template 11 | from server.app import app 12 | from server import models 13 | from server import mysql 14 | 15 | database=mysql.database() 16 | mydata = "" 17 | 18 | @app.route("/api/v1", methods=["GET"]) 19 | def parse(): 20 | global mydata 21 | req = request.args 22 | # .args.get('username') 23 | if "car_name" in req: 24 | name = req["car_name"] 25 | mydata = models.execute(database,("car_name", name)) 26 | ''' 27 | elif "relation" in req: 28 | name = req["relation"] 29 | mydata = models.execute(database,("relation", name)) 30 | ''' 31 | # return {"resultmsg":"OK","resultno":ERROR_OK},200 32 | # 模板的位置放在templates文件夹下面 33 | return render_template('index.html') 34 | 35 | @app.route("/api/data") 36 | def data(): 37 | return mydata 38 | 39 | -------------------------------------------------------------------------------- /汽车行业知识图谱第一次验收/效果.PNG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/qiu997018209/KnowledgeGraph/5d91826c2346b9f9f301f99278e98464d79fbb4b/汽车行业知识图谱第一次验收/效果.PNG -------------------------------------------------------------------------------- /汽车行业知识图谱第二次验收/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/qiu997018209/KnowledgeGraph/5d91826c2346b9f9f301f99278e98464d79fbb4b/汽车行业知识图谱第二次验收/__init__.py -------------------------------------------------------------------------------- /汽车行业知识图谱第二次验收/conf.py: -------------------------------------------------------------------------------- 1 | #coding:utf-8 2 | ''' 3 | Created on 2017年12月11日 4 | 5 | @author: qiujiahao 6 | 7 | @email:997018209@qq.com 8 | 9 | ''' 10 | #数据路径 11 | 12 | import argparse 13 | 14 | def get_args(): 15 | parser = argparse.ArgumentParser() 16 | parser.add_argument('-nu','--neo4j_user', help='neo4j的用户名',type=str,default='neo4j') 17 | parser.add_argument('-np','--neo4j_password', help='neo4j的密码',type=str,default='123456') 18 | parser.add_argument('-p','--http_port', help='http端口',type=int,default='8080') 19 | args = parser.parse_args() 20 | return args 21 | 22 | 23 | 24 | 25 | -------------------------------------------------------------------------------- /汽车行业知识图谱第二次验收/data/http接口说明.txt: -------------------------------------------------------------------------------- 1 | 1.查询单个实体： 2 | 说明: 3 | 1.deep代表查找的深度，一般不要超过3,最小为1，建议默认为3 4 | 2.edges中的每一列，代表一条边，第一个为起始点，第二个为关系，第三个为终点 5 | 3.当success为false的时候代表没有查找到数据 6 | 举例: 7 | 输入:{"method":'entry','id':1,'jsonrpc':2.0,"params":{'name':'英朗','deep':3}} 8 | 输出:{'method': 'entry', 'id': 1, 'jsonrpc': 2.0, 'result': {'edges': [['前轮驱动', '中文名', '前轮驱动'], ['捷达', '驱动方式', '前轮驱动'], ['别克君越', '品牌', '别克'], ['红旗旗舰', '驱动方式', '前轮驱动'], ['英朗', '驱动方式', '前轮驱动'], ['英朗', '油耗', '7.4L/100KM'], ['一汽', '所属行业', '汽车制造'], ['重锤', '制片地区', '美国'], ['日产天籁', '标准座位数', '5座'], ['雪佛兰景程', '驱动方式', '前轮驱动'], ['斯柯达晶锐', '驱动方式', '前轮驱动'], ['前轮驱动', '性质', '动力分配方式'], ['骐达', '驱动方式', '前轮驱动'], ['威利斯', '国家', '美国'], ['英菲尼迪', '经营范围', '汽车制造'], ['新君威', '驱动方式', '前轮驱动'], ['吉利帝豪', '驱动方式', '前轮驱动'], ['双环汽车', '经营范围', '汽车制造'], ['尚酷', '驱动方式', '前轮驱动'], ['山地自行车', '起源地', '美国'], ['斯柯达速派', '标准座位数', '5座'], ['火鸟', '每集长度', '60'], ['长城', '制片地区', '美国'], ['现代途胜', '驱动方式', '前轮驱动'], ['高尔', '驱动方式', '前轮驱动'], ['福莱尔', '标准座位数', '5座'], ['本田思域', '驱动方式', '前轮驱动'], ['索诺马', '总部', '美国'], ['帕萨特领驭', '驱动方式', '前轮驱动'], ['别克', '总部地点', '美国'], ['陆尊', '品牌', '别克'], ['富康', '驱动方式', '前轮驱动'], ['爱丽丝', '国籍', '美国'], ['菲亚特', '经营范围', '汽车制造'], ['英菲尼迪', '创立地点', '美国'], ['威志', '驱动方式', '前轮驱动'], ['指挥官', '制片地区', '美国'], ['别克', '经营范围', '中高端汽车生产'], ['驱动齿轮', '地区：', '美国'], ['英朗', '引擎类型', '自然吸气涡轮增压'], ['速腾', '驱动方式', '前轮驱动'], ['雷诺', '经营范围', '中高端汽车生产'], ['朗逸', '驱动方式', '前轮驱动'], ['道奇', '国别', '美国'], ['大捷龙', '驱动方式', '前轮驱动'], ['双龙爱腾', '标准座位数', '5座'], ['尊驰', '驱动方式', '前轮驱动'], ['昂克雷', '生产厂商', '别克'], ['大众迈腾', '驱动方式', '前轮驱动'], ['英朗', '行李舱容积', '375L'], ['蒙迪欧致胜', '驱动型式', '前轮驱动'], ['帕诺兹', '经营范围', '汽车制造'], ['盾牌', '制片地区', '美国'], ['雪佛兰', '国别', '美国'], ['安全气囊', '发明国家', '美国'], ['亚伯拉罕·林肯', '国籍', '美国'], ['前轮驱动', '外文名', 'FRONTWHEELDRIVE'], ['赛欧', '驱动方式', '前轮驱动'], ['福特', '经营范围', '中高端汽车生产'], ['福特S-MAX', '驱动方式', '前轮驱动'], ['前轮驱动', '特点', '发动机只驱动一对前轮'], ['蓝瑟·翼神', '驱动方式', '前轮驱动'], ['超人前传', '制片地区', '美国'], ['悦动', '驱动方式', '前轮驱动'], ['颐达', '驱动方式', '前轮驱动'], ['北京吉普', '所属行业', '汽车制造'], ['前轮驱动', '属于', '汽车设计'], ['斯柯达昊锐', '驱动方式', '前轮驱动'], ['雪佛兰科帕奇', '生产厂商', '上海通用'], ['江淮和悦', '驱动方式', '前轮驱动'], ['路虎', '成立时间', '1904年'], ['别克昂科威', '品牌', '别克'], ['吉利', '经营范围', '汽车制造'], ['英朗', '车身重量', '1430'], ['日产骏逸', '驱动方式', '前轮驱动'], ['宝骏乐驰', '驱动方式', '前轮驱动'], ['英朗', '轴距', '2685'], ['贵士', '驱动方式', '前轮驱动'], ['摩根·弗里曼', '国籍', '美国'], ['福特蒙迪欧', '标准座位数', '5座'], ['力矩扳手', '起源于', '美国'], ['别克', '品牌定位', '豪华品牌'], ['宝来', '驱动方式', '前轮驱动'], ['富康', '标准座位数', '5座'], ['猎豹飞腾', '驱动方式', '前轮驱动'], ['英朗', '生产厂商', '上海通用'], ['别克', '公司名称', '别克汽车公司'], ['优派', '国别', '美国'], ['开瑞', '驱动方式', '前轮驱动'], ['英朗', '车型尺寸', '4419*1814*1487'], ['雪佛兰科鲁兹', '驱动方式', '前轮驱动'], ['别克', '成立时间', '1904年'], ['别克', '创始人', '大卫·邓巴·别克'], ['新君威', '生产厂商', '上海通用'], ['别克君威', '品牌', '别克'], ['英朗', '油箱容积', '60'], ['自由舰', '驱动方式', '前轮驱动'], ['海福星', '驱动方式', '前轮驱动'], ['途安', '驱动方式', '前轮驱动'], ['赛影', '标准座位数', '5座'], ['长安之星', '驱动方式', '前轮驱动'], ['英朗', '参考价格', '12.99-18.73'], ['英朗', '标准座位数', '5座'], ['别克君越', '生产厂商', '上海通用'], ['斯巴鲁傲虎', '标准座位数', '5座'], ['别克昂科雷', '所属品牌', '别克'], ['一汽大众', '经营范围', '汽车制造'], ['别克', '公司性质', '汽车制造'], ['福美来', '标准座位数', '5座'], ['守卫者', '国籍', '美国'], ['菱悦', '驱动方式', '前轮驱动'], ['雅阁', '驱动方式', '前轮驱动'], ['威利斯', '马力', '60'], ['英朗', '加速时间', '12.3'], ['长安杰勋', '驱动方式', '前轮驱动'], ['别克', '外文名称', 'BUICK'], ['霍顿', '经营范围', '汽车制造'], ['新佳乐', '驱动方式', '前轮驱动'], ['泰肖恩·普林斯', '国籍', '美国'], ['别克', '公司口号', '心静，思远，志行千里'], ['英朗', '最高时速', '210'], ['英朗', '品牌', '别克'], ['锐欧', '标准座位数', '5座']], 'success': 'true'}} 9 | 10 | 2.查询统计信息： 11 | 说明:total_nums代表当前数据库里有多少个实体，api_nums代表图数据库被调用的次数 12 | 举例: 13 | 输入:{"method":'statistics','id':1,'jsonrpc':2.0} 14 | 输出:{'method': 'statistics', 'id': 1, 'jsonrpc': 2.0, 'result': {'total_nums': 11039, 'success': 'true', 'api_nums': 45}} 15 | 16 | 3.查询实体与实体间的关系: 17 | 说明: 18 | 1.当success为false的时候代表没有查找到数据 19 | 2.edges中的每一列，代表一条边，第一个为起始点，第二个为关系，第三个为终点 20 | 举例: 21 | 输入:{"method":'entry_to_entry','id':1,'jsonrpc':2.0,"params":{'entry1':'英朗','entry2':'前轮驱动'}} 22 | 输出:{'method': 'entry_to_entry', 'id': 1, 'jsonrpc': 2.0, 'result': {'edges': [['英朗', '驱动方式', '前轮驱动']], 'success': 'true'}} 23 | 24 | 4.查询实体与属性的关系： 25 | 说明: 26 | 1.当success为false的时候代表没有查找到数据 27 | 2.edges中的每一列，代表一条边，第一个为起始点，第二个为关系，第三个为终点 28 | 举例: 29 | 输入:{"method":'entry_to_property','id':1,'jsonrpc':2.0,"params":{'entry':'英朗','property':'驱动方式'}} 30 | 输出:{'method': 'entry_to_property', 'id': 1, 'jsonrpc': 2.0, 'result': {'edges': [['英朗', '驱动方式', '前轮驱动']], 'success': 'true'}} 31 | 5.查询当前接口是否可用: 32 | 输入:{"method":'live','id':1,'jsonrpc':2.0} 33 | 输出:{'result': {'success': 'true'}, 'jsonrpc': 2.0, 'method': 'live', 'id': 1} 34 | -------------------------------------------------------------------------------- /汽车行业知识图谱第二次验收/data/statistics.txt: -------------------------------------------------------------------------------- 1 | 0 2 | -------------------------------------------------------------------------------- /汽车行业知识图谱第二次验收/kg/kg.py: -------------------------------------------------------------------------------- 1 | #coding:utf-8 2 | ''' 3 | Created on 2018年1月26日 4 | 5 | @author: qiujiahao 6 | 7 | @email:997018209@qq.com 8 | 9 | ''' 10 | import sys 11 | import re 12 | sys.path.append('..') 13 | from conf import get_args 14 | from py2neo import Node,Relationship,size,order,Graph,NodeSelector 15 | 16 | class data(object): 17 | def __init__(self): 18 | self.args=get_args() 19 | self.data_process() 20 | 21 | def data_process(self): 22 | #初始化操作 23 | self.data_init() 24 | 25 | #插入数据 26 | self.insert_datas() 27 | 28 | 29 | def data_init(self): 30 | #连接图数据库 31 | print('开始数据预处理') 32 | self.graph = Graph('127.0.0.1:7474',user=self.args.neo4j_user,password=self.args.neo4j_password) 33 | self.selector=NodeSelector(self.graph) 34 | self.graph.delete_all() 35 | 36 | def insert_datas(self): 37 | print('开始插入数据') 38 | with open('../data/three_tuples.txt','r',encoding='utf-8') as f: 39 | lines,num=f.readlines(),-1 40 | for line in lines: 41 | num+=1 42 | if num%500==0: 43 | print('当前处理进度:{}/{}'.format(lines.index(line),len(lines))) 44 | line=line.strip().split('\t') 45 | if len(line)!=3: 46 | print('insert_datas错误:',line) 47 | continue 48 | self.insert_one_data(line) 49 | 50 | 51 | def insert_one_data(self,line): 52 | if '' in line: 53 | print('insert_one_data错误',line) 54 | return 55 | 56 | start=self.look_and_create(line[0]) 57 | for name in self.get_items(line[2]): 58 | end=self.look_and_create(name) 59 | r=Relationship(start,line[1],end,name=line[1]) 60 | self.graph.create(r)#当存在时不会创建新的 61 | 62 | #查找节点是否不存，不存在就创建一个 63 | def look_and_create(self,name): 64 | end=self.graph.find_one(label="car_industry",property_key="name",property_value=name) 65 | if end==None: 66 | end=Node('car_industry',name=name) 67 | return end 68 | 69 | def get_items(self,line): 70 | if '{' not in line and '}' not in line: 71 | return [line] 72 | #检查 73 | if '{' not in line or '}' not in line: 74 | print('get_items Error',line) 75 | lines= [w[1:-1] for w in re.findall('{.*?}',line)] 76 | return lines 77 | 78 | if __name__=='__main__': 79 | data=data() 80 | 81 | -------------------------------------------------------------------------------- /汽车行业知识图谱第二次验收/kg/kg_test.py: -------------------------------------------------------------------------------- 1 | #coding:utf-8 2 | ''' 3 | Created on 2018年1月25日 4 | 5 | @author: qiujiahao 6 | 7 | @email:997018209@qq.com 8 | 9 | ''' 10 | from py2neo import Node,Relationship,size,order,Graph,NodeSelector 11 | 12 | #graph = Graph('127.0.0.1:7474',user='neo4j',password='123456') 13 | ''' 14 | 常用API 15 | graph.delete_all() 删除所有的节点和关系 16 | graph.data("MATCH (n) RETURN n") 调用Cypher查询语言 17 | 18 | a=Node('Person',name='Mike',age=21,location='广州') 19 | b=Node('Person',name='Bob',age=22,location='上海') 20 | c=Node('Person',name='Alice',age=21,location='北京') 21 | r1=Relationship(a,'KNOWS',b) 22 | r2=Relationship(b,'KNOWS',c) 23 | graph.create(a|b|c|r1|r2) 24 | 25 | selector=NodeSelector(graph)#会找出所有的关系 26 | #persons=selector.select('Person',age=21) 27 | #print(list(persons)) 28 | #使用正则表达式进行查找 29 | persons=selector.select('Person').where("_.name =~ 'A.*'") 30 | print(list(persons)) 31 | #查找单个节点 32 | persons=selector.select('Person').where("_.name =~ 'A.*'").first() 33 | print(list(persons)) 34 | 35 | #查找一个 36 | relations=graph.match_one(rel_type='KNOWS') 37 | print(relations) 38 | 39 | #排序 40 | selector=NodeSelector(graph)#会找出所有的关系 41 | persons=selector.select('Person').order_by('_.age') 42 | print(list(persons)) 43 | 44 | #运行Cyper语句 45 | data=graph.run('MATCH (p:Person) RETURN p LIMIT 5') 46 | print(list(data)) 47 | 48 | ''' 49 | ''' 50 | #OGM可以实现一个对象和Node的关联 51 | from py2neo.ogm import GraphObject,Property,RelatedTo 52 | 53 | class Person(GraphObject): 54 | __primarykey__='name'#默认是id,设置主键的好处是push数据的时候不会重复添加 55 | name=Property() 56 | age=Property() 57 | location=Property() 58 | knows=RelatedTo('Person','KNOWS') 59 | 60 | person=Person.select(graph).where(age=20).first() 61 | print(person) 62 | print(person.name) 63 | print(person.location) 64 | person.age=20 65 | print(person.__ogm__.node) 66 | graph.push(person) 67 | print(list(person.knows)) 68 | 69 | new_person=Person() 70 | new_person.name='Durant' 71 | new_person.age=28 72 | person.knows.add(new_person) 73 | print(list(person.knows)) 74 | graph.push(person)#添加到数据库 75 | 76 | target=Person.select(graph).where(name='Durant').first() 77 | print(list(person.knows)) 78 | person.knows.remove(target)#删除节点间的关系 79 | print(list(person.knows)) 80 | 81 | graph.push(person) 82 | graph.delete(target)#先删除节点上的关系，才能删除节点 83 | 84 | graph.delete_all() 85 | b=Node('Person',name='Bob',age=22,location='上海') 86 | a=Node('Person',name='Bob2',age=22,location='上海') 87 | c=Node('Person',name='Bob2',age=22,location='上海') 88 | r1=Relationship(a,'KNOWS',b) 89 | graph.create(r1) 90 | r2=Relationship(a,'KNOWS',c) 91 | graph.create(r2) 92 | 93 | c=Node('Person',name='Bob3',age=22,location='上海') 94 | r1=Relationship(a,'KNOWS',c) 95 | graph.create(r1) 96 | r1=Relationship(c,'KNOWS',b) 97 | graph.create(r1) 98 | #graph.push(b) 99 | ''' 100 | ''' 101 | with open('../data/three_tuples.txt','r',encoding='utf-8') as f: 102 | with open('three_tuples.txt','w',encoding='utf-8') as f2: 103 | for line in f.readlines(): 104 | line=line.strip() 105 | line=line.split(':') 106 | try: 107 | f2.write('{}\t{}\t{}\n'.format(line[0],line[1],''.join(line[2:]))) 108 | except: 109 | f2.write(''.join(line)) 110 | 111 | ''' 112 | 113 | 114 | 115 | 116 | 117 | 118 | 119 | -------------------------------------------------------------------------------- /汽车行业知识图谱第二次验收/readme.txt: -------------------------------------------------------------------------------- 1 | 1.基于知识图谱的问答系统: 2 | 目前通过前端限定用户通过指定的格式来输入问题，然后通过查询知识图谱的形式来回答 3 | 4 | 5 | 2.本次跟新介绍: 6 | 1.考虑到后续数据量大，将数据库从Mysql替换为Neo4j 7 | 2.新增5个http接口 8 | 3.支持多层查询与存储，考虑到查询的时间消耗，建议不超过3层 9 | 10 | 3.http接口说明: 11 | 详细说明:data/http接口说明.txt 12 | 1.查询单个实体,支持查询深度限制,深度为3时，查询时间为3.5s，深度为4时，查询时间为85s。 13 | 2.查询两个实体间的关系 14 | 3.查询单个实体的某个属性值 15 | 4.统计当前数据库里有多少个实体以及当前数据库被访问多少次 16 | 5.当前接口是否可用 17 | 18 | 4.环境: 19 | python3+Neo4j+flask 20 | 21 | 5.运行: 22 | 1.启动数据库:neo4j console 23 | 2.插入数据:kg/kg.py,数据格式:data/three_tuples.txt 24 | 3.提供web服务:python3 server/run_server.py 25 | 26 | 6.效果:效果.PNG 27 | 28 | 29 | 7.后续改进可能: 30 | 1.通过知识图谱三元组与原始输入的向量之间利用深度学习求相似度，找到最相近的三元组，作为答案，达到准确率的要求后再给出答案 31 | 2.但考虑到在实际使用时，本方案会与所有三元组计算一下相似度，时间消耗较大，因此需要命名实体识别，先找出相关的一部分三元组，再求相似 -------------------------------------------------------------------------------- /汽车行业知识图谱第二次验收/server/.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/qiu997018209/KnowledgeGraph/5d91826c2346b9f9f301f99278e98464d79fbb4b/汽车行业知识图谱第二次验收/server/.DS_Store -------------------------------------------------------------------------------- /汽车行业知识图谱第二次验收/server/__init__.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | 3 | 4 | -------------------------------------------------------------------------------- /汽车行业知识图谱第二次验收/server/app.py: -------------------------------------------------------------------------------- 1 | #coding:utf-8 2 | ''' 3 | Created on 2018年1月9日 4 | 5 | @author: qiujiahao 6 | 7 | @email:997018209@qq.com 8 | 9 | ''' 10 | from flask import Flask 11 | app = Flask(__name__) 12 | from server.views import * -------------------------------------------------------------------------------- /汽车行业知识图谱第二次验收/server/http_test.py: -------------------------------------------------------------------------------- 1 | #coding:utf-8 2 | ''' 3 | Created on 2017年10月9日 4 | 5 | @author: qiujiahao 6 | 7 | @email:997018209@qq.com 8 | 9 | ''' 10 | import requests 11 | import json 12 | s = requests 13 | lookup_entry={"method":'entry','id':1,'jsonrpc':2.0,"params":{'name':'英朗','deep':3}} 14 | lookup_statistics={"method":'statistics','id':1,'jsonrpc':2.0} 15 | lookup_entry2entry={"method":'entry_to_entry','id':1,'jsonrpc':2.0,"params":{'entry1':'英朗','entry2':'前轮驱动'}} 16 | lookup_entry2property={"method":'entry_to_property','id':1,'jsonrpc':2.0,"params":{'entry':'英朗','property':'驱动方式'}} 17 | 18 | 19 | while True: 20 | choice=input('你想测试的方法是:\n1.entry\n2.statistics\n3.entry2entry\n4.entry2property\n:') 21 | if choice=='1': 22 | data=lookup_entry 23 | elif choice=='2': 24 | data=lookup_statistics 25 | elif choice=='3': 26 | data=lookup_entry2entry 27 | elif choice=='4': 28 | data=lookup_entry2property 29 | try: 30 | r = s.post('http://192.168.1.245:1111/KnowGraph/v2', json.dumps(data)) 31 | print (r.status_code) 32 | print (r.headers['content-type']) 33 | r.encoding = 'utf-8' 34 | print (eval(r.text)) 35 | except Exception as e: 36 | print(e) 37 | -------------------------------------------------------------------------------- /汽车行业知识图谱第二次验收/server/module.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | import tensorflow as tf 3 | import numpy as np 4 | import os 5 | import time 6 | from threading import Thread 7 | from py2neo import Node,Relationship,size,order,Graph,NodeSelector 8 | 9 | class KnowGraph(object): 10 | def __init__(self,args): 11 | self.args=args 12 | self.graph = Graph('127.0.0.1:7474',user='neo4j',password='123456') 13 | self.write_to_statistics() 14 | #查找单个实体 15 | def lookup_entry(self,client_params,server_param): 16 | #支持设定网络查找的深度 17 | start_time = time.time() 18 | params=client_params["params"] 19 | edges=set() 20 | self.lookup_entry_deep(edges,params,0) 21 | if len(edges)==0: 22 | server_param['result']={"success":'false'} 23 | else: 24 | server_param['result']={'edges':[list(i) for i in edges],"success":'true'} 25 | print('本次查找三元组的数量为:{},耗时:{}s'.format(len(edges),time.time()-start_time)) 26 | 27 | #查找两个实体间的关系 28 | def lookup_entry2entry(self,client_params,server_param): 29 | params=client_params["params"] 30 | edges=set() 31 | 32 | #考虑到顺序的问题，所以查了四次 33 | result1=self.graph.data("MATCH (s)-[r]->(e) where s.name='{}' and e.name='{}' RETURN s.name,r.name,e.name".format(params['entry1'],params['entry2'])) 34 | result2=self.graph.data("MATCH (s)-[r]->(e) where s.name='{}' and e.name='{}' RETURN s.name,r.name,e.name".format(params['entry2'],params['entry1'])) 35 | 36 | if len(result1)==0 and len(result2)==0: 37 | server_param["result"]={"success":'false'} 38 | return 39 | for item in result1: 40 | edges.add((item['s.name'],item['r.name'],item['e.name'])) 41 | for item in result2: 42 | edges.add((item['s.name'],item['r.name'],item['e.name'])) 43 | 44 | #result=self.graph.data("match (a),(b) where a.name='{}' and b.name='{}' match p = shortestPath((a)-[*..15]-(b))return p".format(params['entry1'],params['entry2'])) 45 | server_param["result"]={'edges':[list(i) for i in edges],"success":'true'} 46 | 47 | #查找指定实体的指定属性 48 | def lookup_entry2property(self,client_params,server_param): 49 | params=client_params["params"] 50 | edges=set() 51 | result1=self.graph.data("MATCH (s)-[r]->(e) where s.name='{}' and r.name='{}' RETURN s.name,r.name,e.name".format(params['entry'],params['property'])) 52 | result2=self.graph.data("MATCH (e)<-[r]-(s) where e.name='{}' and r.name='{}' RETURN s.name,r.name,e.name".format(params['entry'],params['property'])) 53 | if len(result1)==0 and len(result2)==0: 54 | server_param["result"]=[{"success":'false'}] 55 | return 56 | for item in result1: 57 | edges.add((item['s.name'],item['r.name'],item['e.name'])) 58 | for item in result2: 59 | edges.add((item['s.name'],item['r.name'],item['e.name'])) 60 | server_param["result"]={'edges':[list(i) for i in edges],"success":'true'} 61 | 62 | #查询统计信息 63 | def lookup_statistics(self,client_params,server_param): 64 | result=self.graph.data("MATCH (n) RETURN n") 65 | with open('../data/statistics.txt','r',encoding='utf-8') as f: 66 | api_nums=f.readline().strip() 67 | server_param['result']={'total_nums':len(result),'api_nums':api_nums,"success":'true'} 68 | 69 | #统计API访问次数 70 | def write_to_statistics(self): 71 | with open('../data/statistics.txt','r',encoding='utf-8') as f: 72 | api_nums=int(f.readline().strip())+1 73 | with open('../data/statistics.txt','w',encoding='utf-8') as f: 74 | f.write(str(api_nums)+'\n') 75 | 76 | #限制深度的查找 77 | def lookup_entry_deep(self,edges,params,deep): 78 | #当前查找深度不得等于要求的深度 79 | if deep >= params['deep']: 80 | return 81 | #正向查找 82 | result1=self.graph.data("match (s)-[r]->(e) where s.name='{}' return s.name,r.name,e.name".format(params['name'])) 83 | result2=self.graph.data("match (e)<-[r]-(s) where e.name='{}' return s.name,r.name,e.name".format(params['name'])) 84 | if len(result1)==0 and len(result2)==0: 85 | return 86 | for item in result1: 87 | edges.add((item['s.name'],item['r.name'],item['e.name'])) 88 | if item['s.name'] != item['e.name']:#避免出现:双面胶:中文名:双面胶的死循环 89 | params['name']=item['e.name'] 90 | self.lookup_entry_deep(edges,params.copy(),deep+1) 91 | 92 | for item in result2: 93 | edges.add((item['s.name'],item['r.name'],item['e.name'])) 94 | if item['s.name'] != item['e.name']:#避免出现:双面胶:中文名:双面胶的死循环 95 | params['name']=item['e.name'] 96 | self.lookup_entry_deep(edges,params.copy(),deep+1) 97 | -------------------------------------------------------------------------------- /汽车行业知识图谱第二次验收/server/run_server.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | import sys 3 | sys.path.append("..") 4 | from app import app 5 | from conf import * 6 | 7 | if __name__ == '__main__': 8 | args=get_args() 9 | print('\nhttp_host:{},http_port:{}'.format('0.0.0.0',args.http_port)) 10 | app.run(debug=True, host='0.0.0.0', port=args.http_port) 11 | -------------------------------------------------------------------------------- /汽车行业知识图谱第二次验收/server/views.py: -------------------------------------------------------------------------------- 1 | #coding:utf-8 2 | ''' 3 | Created on 2018年1月9日 4 | 5 | @author: qiujiahao 6 | 7 | @email:997018209@qq.com 8 | 9 | ''' 10 | 11 | from flask import jsonify 12 | from conf import * 13 | from flask import Flask 14 | from flask import request 15 | from server.app import app 16 | import tensorflow as tf 17 | from server.module import KnowGraph 18 | import json 19 | 20 | @app.route('/KnowGraph/v2',methods=["POST"]) 21 | def look_up(): 22 | kg=KnowGraph(get_args()) 23 | client_params=request.get_json(force=True) 24 | server_param={} 25 | if client_params['method'] == 'entry_to_entry': 26 | kg.lookup_entry2entry(client_params,server_param) 27 | elif client_params['method'] == 'entry_to_property': 28 | kg.lookup_entry2property(client_params,server_param) 29 | elif client_params['method'] == 'entry': 30 | kg.lookup_entry(client_params,server_param) 31 | elif client_params['method'] == 'statistics': 32 | kg.lookup_statistics(client_params,server_param) 33 | elif client_params['method'] == 'live': 34 | params={'success':'true'} 35 | server_param['result']=params 36 | server_param['id']=client_params['id'] 37 | server_param['jsonrpc']=client_params['jsonrpc'] 38 | server_param['method']=client_params['method'] 39 | print(server_param) 40 | return json.dumps(server_param, ensure_ascii=False).encode("utf-8") -------------------------------------------------------------------------------- /汽车行业知识图谱第二次验收/test.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/qiu997018209/KnowledgeGraph/5d91826c2346b9f9f301f99278e98464d79fbb4b/汽车行业知识图谱第二次验收/test.py -------------------------------------------------------------------------------- /汽车行业知识图谱第二次验收/效果.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/qiu997018209/KnowledgeGraph/5d91826c2346b9f9f301f99278e98464d79fbb4b/汽车行业知识图谱第二次验收/效果.png -------------------------------------------------------------------------------- /知识图谱学习笔记/笔记.docx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/qiu997018209/KnowledgeGraph/5d91826c2346b9f9f301f99278e98464d79fbb4b/知识图谱学习笔记/笔记.docx --------------------------------------------------------------------------------