├── ._README.md ├── README.pdf ├── ._README.pdf ├── images ├── idea01.png └── idea02.png ├── requirements.txt ├── static ├── images │ ├── bored.gif │ ├── orb2.png │ ├── mute_off.png │ ├── mute_on.png │ ├── speaking.gif │ └── waiting.gif ├── index.html ├── css │ ├── css.css │ └── chatbot.css └── js │ ├── chatbot.js │ └── jquery-2.1.4.min.js ├── questions ├── ._userdict3.txt ├── ._vocabulary.txt ├── ._question_classification.txt ├── question_classification.txt ├── label.txt ├── vocabulary.txt └── userdict3.txt ├── __pycache__ ├── preprocess_data.cpython-36.pyc ├── process_question.cpython-36.pyc ├── question_template.cpython-36.pyc └── question_classification.cpython-36.pyc ├── .idea ├── vcs.xml ├── modules.xml ├── misc.xml ├── Movie-QA-System.iml ├── inspectionProfiles │ └── Project_Default.xml └── workspace.xml ├── data ├── genre.csv └── person.csv ├── test.py ├── client.py ├── server.py ├── question_classification.py ├── data2neo4j.py ├── README.md ├── process_question.py └── question_template.py /._README.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/xiaoliang8006/Movie-QA-System/HEAD/._README.md -------------------------------------------------------------------------------- /README.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/xiaoliang8006/Movie-QA-System/HEAD/README.pdf -------------------------------------------------------------------------------- /._README.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/xiaoliang8006/Movie-QA-System/HEAD/._README.pdf -------------------------------------------------------------------------------- /images/idea01.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/xiaoliang8006/Movie-QA-System/HEAD/images/idea01.png 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-------------------------------------------------------------------------------- 1 | gid,gname 2 | 12,冒险 3 | 14,奇幻 4 | 16,动画 5 | 18,剧情 6 | 27,恐怖 7 | 28,动作 8 | 35,喜剧 9 | 36,历史 10 | 37,西部 11 | 53,惊悚 12 | 80,犯罪 13 | 99,纪录 14 | 878,科幻 15 | 9648,悬疑 16 | 10402,音乐 17 | 10749,爱情 18 | 10751,家庭 19 | 10752,战争 20 | 10770,电视电影 21 | -------------------------------------------------------------------------------- /questions/question_classification.txt: -------------------------------------------------------------------------------- 1 | 0:nm 评分 2 | 1:nm 上映时间 3 | 2:nm 类型 4 | 3:nm 简介 5 | 4:nm 演员列表 6 | 5:nnt 介绍 7 | 6:nnt ng 电影作品 8 | 7:nnt 电影作品 9 | 8:nnt 参演评分 大于 x 10 | 9:nnt 参演评分 小于 x 11 | 10:nnt 电影类型 12 | 11:nnt nnr 合作 电影列表 13 | 12:nnt 电影数量 14 | 13:nnt 出生日期 -------------------------------------------------------------------------------- /.idea/modules.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | -------------------------------------------------------------------------------- /.idea/misc.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 6 | 7 | -------------------------------------------------------------------------------- /test.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | 3 | 4 | import sys 5 | from process_question import Question 6 | # 创建问题处理对象，这样模型就可以常驻内存 7 | que=Question() 8 | # Restorepip freeze > requirements.txt 9 | def enablePrint(): 10 | sys.stdout = sys.__stdout__ 11 | enablePrint() 12 | 13 | 14 | result=que.question_process("李连杰生日是哪天？") 15 | print(result) 16 | -------------------------------------------------------------------------------- /client.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | import requests 3 | import json 4 | 5 | 6 | def Chat(): 7 | print("Robot: 您好，有什么需要帮助的吗？[输入0退出]") 8 | while True: 9 | text=input("Me: ") 10 | if text=='0': 11 | print("Robot: 再见～") 12 | break 13 | url="http://127.0.0.1:5000/search?q="+text 14 | response = requests.get(url) 15 | result = json.loads(response.content)['answer'] 16 | print("Robot:",result) 17 | 18 | if __name__ == '__main__': 19 | Chat() 20 | -------------------------------------------------------------------------------- /.idea/Movie-QA-System.iml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 11 | 12 | 15 | -------------------------------------------------------------------------------- /.idea/inspectionProfiles/Project_Default.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 17 | -------------------------------------------------------------------------------- /server.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | import json 3 | from flask import Flask,request 4 | import sys 5 | from process_question import Question 6 | 7 | 8 | def after_request(response): 9 | response.headers['Access-Control-Allow-Origin'] = '*' 10 | response.headers['Access-Control-Allow-Methods'] = 'PUT,GET,POST,DELETE' 11 | response.headers['Access-Control-Allow-Headers'] = 'Content-Type,Authorization' 12 | return response 13 | 14 | app = Flask(__name__,static_url_path="") 15 | app.after_request(after_request) 16 | 17 | # 创建问题处理对象，这样模型就可以常驻内存 18 | que=Question() 19 | # Restore 20 | def enablePrint(): 21 | sys.stdout = sys.__stdout__ 22 | enablePrint() 23 | 24 | 25 | @app.route('/') 26 | def index(): 27 | return app.send_static_file('index.html') 28 | 29 | # http://127.0.0.1:5000/search?q=你好 30 | @app.route('/search') 31 | def search(): 32 | text = request.args.get('q') 33 | answer=que.question_process(text) 34 | res = json.dumps({"answer":answer}) 35 | return res 36 | 37 | 38 | if __name__ == '__main__': 39 | #部署到服务器时host要改成'0.0.0.0' 40 | app.run(debug=False, host='127.0.0.1', port=5000) 41 | -------------------------------------------------------------------------------- /static/index.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | Chatbot 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 |
15 | 21 | 22 |
23 | 24 | 25 |
26 | 27 |
28 |
29 | 30 | 31 |
SEND
32 | 33 |
34 | 35 | 36 | -------------------------------------------------------------------------------- /question_classification.py: -------------------------------------------------------------------------------- 1 | #-*- coding: UTF-8 -*- 2 | #对问题进行分类 3 | 4 | from sklearn.naive_bayes import MultinomialNB 5 | from sklearn.feature_extraction.text import TfidfVectorizer 6 | import jieba 7 | 8 | 9 | class Question_classify(): 10 | def __init__(self): 11 | # 读取训练数据 12 | self.train_x,self.train_y=self.read_train_data() 13 | # 训练模型 14 | self.model=self.train_model_NB() 15 | # 获取训练数据 16 | def read_train_data(self): 17 | train_x=[] 18 | train_y=[] 19 | # 读取文件内容 20 | with(open("./questions/label.txt", "r", encoding="utf-8")) as fr: 21 | lines = fr.readlines() 22 | for one_line in lines: 23 | temp = one_line.split(' ') 24 | #print(temp) 25 | word_list=list(jieba.cut(str(temp[1]).strip())) 26 | # 将这一行加入结果集 27 | train_x.append(" ".join(word_list)) 28 | train_y.append(temp[0]) 29 | return train_x,train_y 30 | 31 | # 训练并测试模型-NB 32 | def train_model_NB(self): 33 | X_train, y_train = self.train_x, self.train_y 34 | self.tv = TfidfVectorizer() 35 | 36 | train_data = self.tv.fit_transform(X_train).toarray() 37 | clf = MultinomialNB(alpha=0.01) 38 | clf.fit(train_data, y_train) 39 | return clf 40 | 41 | # 预测 42 | def predict(self,question): 43 | question=[" ".join(list(jieba.cut(question)))] 44 | test_data=self.tv.transform(question).toarray() 45 | y_predict = self.model.predict(test_data)[0] 46 | print("questions type:",y_predict) 47 | return int(y_predict) 48 | 49 | if __name__ == '__main__': 50 | qc=Question_classify() 51 | qc.predict("暗道上映时间") 52 | -------------------------------------------------------------------------------- /data2neo4j.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | ''' 3 | 将csv文件导入neo4j数据库 4 | import文件夹是neo4j默认的数据导入文件夹 5 | 所以首先要将data文件夹下所有csv文件拷贝到neo4j数据库的根目录import文件夹下，没有则先创建import文件夹 6 | 然后运行此程序 7 | ''' 8 | 9 | 10 | from py2neo import Graph 11 | graph = Graph(host="127.0.0.1",port=7474,user="neo4j",password="123456") 12 | 13 | """ 14 | #测试 15 | cql=''' 16 | MATCH (p:Person) 17 | where p.name="张柏芝" 18 | return p 19 | ''' 20 | #清空数据库 21 | #data = graph.run('MATCH (n) OPTIONAL MATCH (n)-[r]-() DELETE n,r') 22 | data = graph.run(cql) 23 | print(list(data)[0]['p']["biography"]) 24 | """ 25 | 26 | #导入节点 电影类型 == 注意类型转换 27 | cql=''' 28 | LOAD CSV WITH HEADERS FROM "file:///genre.csv" AS line 29 | MERGE (p:Genre{gid:toInteger(line.gid),name:line.gname}) 30 | ''' 31 | result = graph.run(cql) 32 | print(result,"电影类型 存储成功") 33 | 34 | #导入节点 演员信息 35 | cql=''' 36 | LOAD CSV WITH HEADERS FROM 'file:///person.csv' AS line 37 | MERGE (p:Person { pid:toInteger(line.pid),birth:line.birth, 38 | death:line.death,name:line.name, 39 | biography:line.biography, 40 | birthplace:line.birthplace}) 41 | ''' 42 | result = graph.run(cql) 43 | print(result,"演员信息 存储成功") 44 | 45 | #导入节点 电影信息 46 | cql=''' 47 | LOAD CSV WITH HEADERS FROM "file:///movie.csv" AS line 48 | MERGE (p:Movie{mid:toInteger(line.mid),title:line.title,introduction:line.introduction, 49 | rating:toFloat(line.rating),releasedate:line.releasedate}) 50 | ''' 51 | result = graph.run(cql) 52 | print(result,"电影信息 存储成功") 53 | 54 | #导入关系 actedin 电影是谁参演的 1对多 55 | cql=''' 56 | LOAD CSV WITH HEADERS FROM "file:///person_to_movie.csv" AS line 57 | match (from:Person{pid:toInteger(line.pid)}),(to:Movie{mid:toInteger(line.mid)}) 58 | merge (from)-[r:actedin{pid:toInteger(line.pid),mid:toInteger(line.mid)}]->(to) 59 | ''' 60 | result = graph.run(cql) 61 | print(result,"电影信息<-->演员信息 存储成功") 62 | 63 | #导入关系 is 电影是什么类型 == 1对多 64 | cql=''' 65 | LOAD CSV WITH HEADERS FROM "file:///movie_to_genre.csv" AS line 66 | match (from:Movie{mid:toInteger(line.mid)}),(to:Genre{gid:toInteger(line.gid)}) 67 | merge (from)-[r:is{mid:toInteger(line.mid),gid:toInteger(line.gid)}]->(to) 68 | ''' 69 | result = graph.run(cql) 70 | print(result,"电影信息<-->电影类型 存储成功") 71 | -------------------------------------------------------------------------------- /questions/label.txt: -------------------------------------------------------------------------------- 1 | 0 nm的评分是多少 2 | 0 nm得了多少分 3 | 0 nm的评分有多少 4 | 0 nm的评分 5 | 0 nm的分数是 6 | 0 nm电影分数是多少 7 | 0 nm评分 8 | 0 nm的分数是多少 9 | 0 nm这部电影的评分是多少 10 | 1 nm的上映时间是什么时候 11 | 1 nm的首映时间是什么时候 12 | 1 nm什么时候上映 13 | 1 nm什么时候首映 14 | 1 nm什么时候在影院上线 15 | 1 什么时候可以在影院看到nm 16 | 1 nm什么时候在影院放映 17 | 1 nm什么时候首播 18 | 2 nm的风格是什么 19 | 2 nm是什么风格的电影 20 | 2 nm的格调是什么 21 | 2 nm是什么格调的电影 22 | 2 nm是什么类型的电影 23 | 2 nm的类型是什么 24 | 2 nm是什么类型的 25 | 3 nm的剧情是什么 26 | 3 nm主要讲什么内容 27 | 3 nm的主要剧情是什么 28 | 3 nm主要讲什么故事 29 | 3 nm的故事线索是什么 30 | 3 nm讲了什么 31 | 3 nm的剧情简介 32 | 3 nm的故事内容 33 | 3 nm的主要情节 34 | 3 nm的情节梗概 35 | 3 nm的故事梗概 36 | 4 nm有哪些演员出演 37 | 4 nm是由哪些人演的 38 | 4 nm中参演的演员都有哪些 39 | 4 nm中哪些人演过 40 | 4 nm这部电影的演员都有哪些 41 | 4 nm这部电影中哪些人演过 42 | 5 nnt 43 | 5 nnt是 44 | 5 nnt是谁 45 | 5 nnt的介绍 46 | 5 nnt的简介 47 | 5 谁是nnt 48 | 5 nnt的详细信息 49 | 5 nnt的信息 50 | 6 nnt演过哪些ng电影 51 | 6 nnt演哪些ng电影 52 | 6 nnt演过ng电影 53 | 6 nnt演过什么ng电影 54 | 6 nnt演过ng电影 55 | 6 nnt演过的ng电影有哪些 56 | 6 nnt出演的ng电影有哪些 57 | 7 nnt演了什么电影 58 | 7 nnt出演了什么电影 59 | 7 nnt演过什么电影 60 | 7 nnt演过哪些电影 61 | 7 nnt过去演过哪些电影 62 | 7 nnt以前演过哪些电影 63 | 7 nnt演过的电影有什么 64 | 7 nnt有哪些电影 65 | 8 nnt参演的评分大于x的电影有哪些 66 | 8 nnt参演的电影评分大于x的有哪些 67 | 8 nnt参演的电影评分超过x的有哪些 68 | 8 nnt演的电影评分超过x的有哪些 69 | 8 nnt演的电影评分大于x的都有哪些 70 | 8 nnt演的电影评分在x以上的都有哪些 71 | 9 nnt参演的评分小于x的电影有哪些 72 | 9 nnt参演的电影评分小于x的有哪些 73 | 9 nnt参演的电影评分低于x的有哪些 74 | 9 nnt演的电影评分低于x的有哪些 75 | 9 nnt演的电影评分小于x的都有哪些 76 | 9 nnt演的电影评分在x以下的都有哪些 77 | 10 nnt演过哪些风格的电影 78 | 10 nnt演过的电影都有哪些风格 79 | 10 nnt演过的电影有哪些类型 80 | 10 nnt演过风格的电影 81 | 10 nnt演过类型的电影 82 | 10 nnt和nnr合作的电影有哪些 83 | 11 nnt和nnr一起拍了哪些电影 84 | 11 nnt和nnr一起演过哪些电影 85 | 11 nnt与nnr合拍了哪些电影 86 | 11 nnt和nnr合作了哪些电影nnt演过题材的电影 87 | 12 nnt一共参演过多少电影 88 | 12 nnt演过多少部电影 89 | 12 nnt演过多少电影 90 | 12 nnt参演的电影有多少 91 | 13 nnt的出生日期 92 | 13 nnt的生日 93 | 13 nnt生日多少 94 | 13 nnt的出生是什么时候 95 | 13 nnt的出生是多少 96 | 13 nnt生日是什么时候 97 | 13 nnt生日什么时候 98 | 13 nnt出生日期是什么时候 99 | 13 nnt什么时候出生的 100 | 13 nnt出生于哪一天 101 | 13 nnt的出生日期是哪一天 102 | 13 nnt哪一天出生的 103 | -------------------------------------------------------------------------------- /questions/vocabulary.txt: -------------------------------------------------------------------------------- 1 | 0:一 2 | 1:地区 3 | 2:谁 4 | 3:口碑 5 | 4:分 6 | 5:哪家 7 | 6:公司 8 | 7:将 9 | 8:上 10 | 9:关键人物 11 | 10:下 12 | 11:准备 13 | 12:推动 14 | 13:喜欢 15 | 14:出品 16 | 15:故事梗概 17 | 16:与 18 | 17:怎么样 19 | 18:演 20 | 19:片长 21 | 20:吗 22 | 21:相同 23 | 22:多 24 | 23:拍摄 25 | 24:影院 26 | 25:拿到 27 | 26:编剧 28 | 27:分数 29 | 28:扮演者 30 | 29:还有 31 | 30:好看 32 | 31:在 33 | 32:哪里 34 | 33:来自 35 | 34:正在 36 | 35:个 37 | 36:背景 38 | 37:成就 39 | 38:中 40 | 39:类似 41 | 40:是 42 | 41:由 43 | 42:当中 44 | 43:剧情 45 | 44:列表 46 | 45:多少 47 | 46:风格 48 | 47:这部 49 | 48:放 50 | 49:分析 51 | 50:简介 52 | 51:时长 53 | 52:重要 54 | 53:片 55 | 54:格调 56 | 55:相似 57 | 56:之中 58 | 57:豆瓣 59 | 58:线索 60 | 59:收获 61 | 60:类似于 62 | 61:情节 63 | 62:网 64 | 63:打 65 | 64:国家 66 | 65:全篇 67 | 66:奖 68 | 67:国人 69 | 68:首映 70 | 69:做 71 | 70:公司出品 72 | 71:上映 73 | 72:多久 74 | 73:这个 75 | 74:出镜率 76 | 75:赢得 77 | 76:步 78 | 77:介绍 79 | 78:扮演 80 | 79:核心人物 81 | 80:受欢迎程度 82 | 81:代表作品 83 | 82:获奖 84 | 83:差不多 85 | 84:相关 86 | 85:影响 87 | 86:未来 88 | 87:执导 89 | 88:类型 90 | 89:影评 91 | 90:计划 92 | 91:要 93 | 92:出版 94 | 93:观众 95 | 94:了 96 | 95:哪个 97 | 96:看到 98 | 97:出生于 99 | 98:制片公司 100 | 99:和 101 | 100:中演 102 | 101:演员表 103 | 102:发行 104 | 103:导演 105 | 104:接受度 106 | 105:热门 107 | 106:得 108 | 107:写 109 | 108:情况 110 | 109:多长时间 111 | 110:什么样 112 | 111:评价 113 | 112:身份 114 | 113:较高 115 | 114:度 116 | 115:生日 117 | 116:题材 118 | 117:主要 119 | 118:多长 120 | 119:放映 121 | 120:发展 122 | 121:走向 123 | 122:时间 124 | 123:讲 125 | 124:筹划 126 | 125:饰演 127 | 126:人 128 | 127:评 129 | 128:首播 130 | 129:过去 131 | 130:梗概 132 | 131:过 133 | 132:演员 134 | 133:拍 135 | 134:经典作品 136 | 135:获得 137 | 136:电影 138 | 137:评分 139 | 138:成绩 140 | 139:网上 141 | 140:票房 142 | 141:高 143 | 142:角色介绍 144 | 143:还 145 | 144:给 146 | 145:个人 147 | 146:哪一天 148 | 147:制片 149 | 148:可以 150 | 149:内容 151 | 150:出品公司 152 | 151:名字 153 | 152:剧情简介 154 | 153:人物 155 | 154:片子 156 | 155:部 157 | 156:奖项 158 | 157:故事 159 | 158:哪 160 | 159:叫 161 | 160:作品 162 | 161:制作 163 | 162:时候 164 | 163:怎么 165 | 164:角色 166 | 165:程度 167 | 166:版权 168 | 167:出生日期 169 | 168:那天 170 | 169:对 171 | 170:即将 172 | 171:出 173 | 172:属于 174 | 173:上线 175 | 174:中的 176 | 175:拿 177 | 176:大于 178 | 177:出生 179 | 178:喜剧 180 | 179:ng 181 | 180:出演 182 | 181:以上 183 | 182:以下 184 | 183:小于 185 | 184:种类 186 | 185:合作 187 | 186:一起 188 | 187:合拍 189 | 188:nnr 190 | 189:信息 -------------------------------------------------------------------------------- /static/css/css.css: -------------------------------------------------------------------------------- 1 | /* cyrillic-ext */ 2 | @font-face { 3 | font-family: 'Roboto Mono'; 4 | font-style: normal; 5 | font-weight: 400; 6 | src: local('Roboto Mono'), local('RobotoMono-Regular'), url(https://fonts.gstatic.com/s/robotomono/v6/L0x5DF4xlVMF-BfR8bXMIjhGq3-cXbKDO1w.woff2) format('woff2'); 7 | unicode-range: U+0460-052F, U+1C80-1C88, U+20B4, U+2DE0-2DFF, U+A640-A69F, U+FE2E-FE2F; 8 | } 9 | /* cyrillic */ 10 | @font-face { 11 | font-family: 'Roboto Mono'; 12 | font-style: normal; 13 | font-weight: 400; 14 | src: local('Roboto Mono'), local('RobotoMono-Regular'), url(https://fonts.gstatic.com/s/robotomono/v6/L0x5DF4xlVMF-BfR8bXMIjhPq3-cXbKDO1w.woff2) format('woff2'); 15 | unicode-range: U+0400-045F, U+0490-0491, U+04B0-04B1, U+2116; 16 | } 17 | /* greek-ext */ 18 | @font-face { 19 | font-family: 'Roboto Mono'; 20 | font-style: normal; 21 | font-weight: 400; 22 | src: local('Roboto Mono'), local('RobotoMono-Regular'), url(https://fonts.gstatic.com/s/robotomono/v6/L0x5DF4xlVMF-BfR8bXMIjhHq3-cXbKDO1w.woff2) format('woff2'); 23 | unicode-range: U+1F00-1FFF; 24 | } 25 | /* greek */ 26 | @font-face { 27 | font-family: 'Roboto Mono'; 28 | font-style: normal; 29 | font-weight: 400; 30 | src: local('Roboto Mono'), local('RobotoMono-Regular'), url(https://fonts.gstatic.com/s/robotomono/v6/L0x5DF4xlVMF-BfR8bXMIjhIq3-cXbKDO1w.woff2) format('woff2'); 31 | unicode-range: U+0370-03FF; 32 | } 33 | /* vietnamese */ 34 | @font-face { 35 | font-family: 'Roboto Mono'; 36 | font-style: normal; 37 | font-weight: 400; 38 | src: local('Roboto Mono'), local('RobotoMono-Regular'), url(https://fonts.gstatic.com/s/robotomono/v6/L0x5DF4xlVMF-BfR8bXMIjhEq3-cXbKDO1w.woff2) format('woff2'); 39 | unicode-range: U+0102-0103, U+0110-0111, U+1EA0-1EF9, U+20AB; 40 | } 41 | /* latin-ext */ 42 | @font-face { 43 | font-family: 'Roboto Mono'; 44 | font-style: normal; 45 | font-weight: 400; 46 | src: local('Roboto Mono'), local('RobotoMono-Regular'), url(https://fonts.gstatic.com/s/robotomono/v6/L0x5DF4xlVMF-BfR8bXMIjhFq3-cXbKDO1w.woff2) format('woff2'); 47 | unicode-range: U+0100-024F, U+0259, U+1E00-1EFF, U+2020, U+20A0-20AB, U+20AD-20CF, U+2113, U+2C60-2C7F, U+A720-A7FF; 48 | } 49 | /* latin */ 50 | @font-face { 51 | font-family: 'Roboto Mono'; 52 | font-style: normal; 53 | font-weight: 400; 54 | src: local('Roboto Mono'), local('RobotoMono-Regular'), url(https://fonts.gstatic.com/s/robotomono/v6/L0x5DF4xlVMF-BfR8bXMIjhLq3-cXbKD.woff2) format('woff2'); 55 | unicode-range: U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+2000-206F, U+2074, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD; 56 | } 57 | -------------------------------------------------------------------------------- /static/js/chatbot.js: -------------------------------------------------------------------------------- 1 | var ChatBot = {}; 2 | 3 | //The server path will be used when sending the chat message to the server. 4 | //todo replace with your server path if needed 5 | ChatBot.SERVER_PATH = window.location.href.slice(0,-1); //"http://localhost:7010"; 6 | ChatBot.userName = "Me"; 7 | 8 | //This function is called in the end of this file 9 | 10 | ChatBot.start = function () { 11 | $(document).ready(function () { 12 | ChatBot.bindUserActions(); 13 | ChatBot.write("你好，有什么需要帮助的吗？", "Robot"); 14 | }); 15 | }; 16 | 17 | ChatBot.bindUserActions = function () { 18 | //Both the "Enter" key and clicking the "Send" button will send the user's message 19 | $('.chat-input').keypress(function (event) { 20 | if (event.keyCode == 13) { 21 | ChatBot.sendMessage(); 22 | } 23 | }); 24 | $(".chat-send").unbind("click").bind("click", function (e) { 25 | ChatBot.sendMessage(); 26 | }); 27 | 28 | }; 29 | 30 | var chatInput="空"; 31 | //The core function of the app, sends the user's line to the server and handling the response 32 | ChatBot.sendMessage = function () { 33 | var sendBtn = $(".chat-send"); 34 | //Do not allow sending a new message while another is being processed 35 | if (!sendBtn.is(".loading")) { 36 | chatInput = $(".chat-input"); 37 | //Only if the user entered a value 38 | if (chatInput.val()) { 39 | console.log("$$$",chatInput.val()); 40 | sendBtn.addClass("loading"); 41 | //写入聊天记录 42 | ChatBot.write(chatInput.val(), ChatBot.userName); 43 | ChatBot.Ajax(); 44 | chatInput.val("") 45 | sendBtn.removeClass("loading"); 46 | } 47 | } 48 | }; 49 | 50 | ChatBot.Ajax = function(){ 51 | $.ajax({ 52 | //部署到服务器时要改成服务器地址http://服务器IP:5000/search 53 | url: "http://127.0.0.1:5000/search", 54 | data: {q: chatInput.val()}, 55 | type: "GET", 56 | dataType: "json", 57 | success: function(data) { 58 | console.log(data); 59 | ChatBot.write(data["answer"], "Robot"); 60 | }, 61 | failed:function() { 62 | console.log("请求失败"); 63 | } 64 | }) 65 | }; 66 | 67 | //写入聊天记录函数 68 | ChatBot.write = function (message, sender, emoji) { 69 | //console.log(message); 70 | var chatScreen = $(".chat-screen"); 71 | sender = $("").addClass("sender").addClass(sender).text(sender + ":"); 72 | var msgContent = $("").addClass("msg").text(message); 73 | var newLine = $("
").addClass("msg-row"); 74 | newLine.append(sender).append(msgContent); 75 | chatScreen.append(newLine); 76 | }; 77 | 78 | 79 | ChatBot.start(); 80 | -------------------------------------------------------------------------------- /static/css/chatbot.css: -------------------------------------------------------------------------------- 1 | body{ 2 | background:#7EC1EE; 3 | font-family:'Roboto Mono'; 4 | } 5 | 6 | .clickable{ 7 | cursor:pointer; 8 | } 9 | 10 | .hidden{ 11 | visibility:hidden; 12 | } 13 | 14 | .shadowed{ 15 | -webkit-box-shadow: 3px 3px 23px 0px rgba(50, 50, 50, 0.75); 16 | -moz-box-shadow: 3px 3px 23px 0px rgba(50, 50, 50, 0.75); 17 | box-shadow: 3px 3px 23px 0px rgba(50, 50, 50, 0.75); 18 | } 19 | 20 | .chat-box{ 21 | display: inline-block; 22 | border-radius: 8px; 23 | padding: 20px; 24 | top: 50%; 25 | transform: translateY(-50%) translateX(-50%); 26 | left: 50%; 27 | position: absolute; 28 | background-color:#B0C4DE; 29 | } 30 | 31 | .chat-window-header{ 32 | font-size: 20px; 33 | line-height: 1.6em; 34 | 35 | background: rgb(255, 255, 255); /* The Fallback */ 36 | background: rgba(122, 122,122, 0.8); 37 | 38 | } 39 | 40 | .chat-screen{ 41 | width:500px; 42 | height:400px; 43 | background-color:white; 44 | border: 1px solid #999; 45 | padding: 10px; 46 | overflow-y: scroll; 47 | } 48 | 49 | .chat-screen .sender{ 50 | color:red; 51 | margin-right: 10px; 52 | } 53 | 54 | .chat-screen .sender.boto{ 55 | color:blue; 56 | } 57 | 58 | 59 | .chat-input{ 60 | width: 380px; 61 | font-size: 20px; 62 | margin-top: 10px; 63 | border: 1px solid #999; 64 | outline: none; 65 | 66 | } 67 | 68 | .chat-send{ 69 | padding:5px 30px; 70 | display:inline-block; 71 | background-color:#00FF7F; 72 | vertical-align: bottom; 73 | } 74 | 75 | .chat-send.loading{ 76 | color: #B0C4DE; 77 | } 78 | 79 | .orb-holder{ 80 | text-align: center; 81 | height: 200px; 82 | position: relative; 83 | } 84 | 85 | .orb{ 86 | position: absolute; 87 | top: 0px; 88 | width: 200px; 89 | left: 50%; 90 | transform: translateX(-50%); 91 | } 92 | 93 | #emoji{ 94 | position: absolute; 95 | top: 0px; 96 | width: 130px; 97 | left: 51%; 98 | top:50%; 99 | transform: translateX(-50%) translateY(-50%); 100 | } 101 | 102 | #mute-btn{ 103 | width: 20px; 104 | height: 20px; 105 | vertical-align: middle; 106 | float: right; 107 | margin-top: 6px; 108 | background-image:url('../images/mute_off.png'); 109 | background-repeat:no-repeat; 110 | background-size:contain; 111 | } 112 | 113 | #mute-btn.on, #mute-btn:hover{ 114 | background-image:url('../images/mute_on.png') ; 115 | } 116 | 117 | #online{ 118 | margin-top:6%; 119 | height:500px; 120 | width:15%; 121 | display:inline-block 122 | margin-left:20px; 123 | padding:1%; 124 | } 125 | 126 | #users{ 127 | top:120px; 128 | background-color:white; 129 | width:14.5%; 130 | height:485px; 131 | 132 | position:absolute; 133 | } 134 | 135 | #onlinenow{ 136 | background-color:lightblue; 137 | color:red; 138 | font-weight:bold; 139 | font-family:arial; 140 | font-size:1.9em; 141 | text-align:center; 142 | display:block; 143 | } 144 | .copyright{ 145 | position: fixed; 146 | bottom: 0px; 147 | left: 0px; 148 | margin: 5px; 149 | } 150 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # 基于知识图谱的电影问答系统 2 | 3 | #### 相关源代码GitHub上也有： 4 | 5 | [https://github.com/xiaoliang8006/Movie-QA-System](https://github.com/xiaoliang8006/Movie-QA-System) 6 | 7 | #### 体验地址： 8 | 9 | [http://104.224.145.185:5000](http://104.224.145.185:5000) 10 | 11 | 此项目旨在构建一个关于电影的知识图谱问答系统。目前知识库本身的内容并不全面，但是麻雀虽小，五脏俱全，该项目对多种类型的问题形式都能得到正确的相应结果。以“李连杰”为例，本系统能够回答晴李连杰的个人简介，参演过的电影，参演过的电影类型，参演某一类型的电影都有什么。还能查询某个电影的信息，如上映时间，评分，类型，演员列表等等.... 12 | 13 | --- 14 | 15 | 提供的功能有： 16 | 17 | * 中文分词 18 | * 词性标注 19 | * 命名实体识别 20 | * 知识图谱关系抽取 21 | * 关键词提取 22 | * 等等.... 23 | 24 | --- 25 | 26 | ## 目录 27 | * [搭建环境](#搭建环境) 28 | * [使用方式](#使用方式) 29 | * [思路](#思路) 30 | * [代码说明](#代码说明) 31 | * [评价](#评价) 32 | * [附录](#附录) 33 | 34 | 35 | ## 搭建环境 36 | 37 | #### python3.6 + jdk1.8 + neo4j-3.4.13 38 | 39 | 注意： neo4j-3.4.13要求java版本必须在jdk8以上 40 | 41 | 网页显示采用flask-0.12.2框架， 和neo4j数据库连接时用的是py2neo-3.0, 之前用py2neo-4.0总是容易出错。 42 | 43 | ## 使用方式 44 | 45 | 先安装依赖: 46 | 47 | pip install -r requirements.txt 48 | 49 | 注意依赖包版本最好和requirements.txt一致或者不要相差太大，不然容易出错。然后运行服务器: 50 | 51 | python server.py 52 | 53 | 最后打开浏览器进入`http://127.0.0.1:5000`即可进行问答。 54 | 55 | 目前本系统可以回答类似如下类型的问题(以李连杰和警察故事为例)： 56 | 57 | 1.警察故事的评分是多少 58 | 2.警察故事的上映时间 59 | 3.警察故事是什么类型的电影 60 | 4.警察故事的主要情节 61 | 5.警察故事中的演员都有谁 62 | 6.李连杰的简介 63 | 7.李连杰演过的动作电影有哪些 64 | 8.李连杰演过哪些电影 65 | 9.李连杰演的电影评分在7以上的都有哪些 66 | 10.李连杰演的电影评分低于7的都有哪些 67 | 11.李连杰演过的电影类型有哪些 68 | 12.李连杰和章子怡一起演过哪些电影 69 | 13.李连杰演过多少部电影 70 | 14.李连杰生日是什么时候 71 | 72 | 73 | ## 思路 74 | 75 | ![images](./images/idea01.png) 76 | ![images](./images/idea02.png) 77 | 78 | ## 代码说明 79 | 80 | #### data文件夹 81 | 82 |     首先是数据的准备，利用爬虫从维基和豆瓣上爬取电影数据及演员数据，这里我直接把数据预处理的结果放入了data文件夹 83 | 84 | #### questions文件夹 85 | 86 |     放的是关于问题分类的训练数据 87 | 88 | #### data2neo4j.py 89 | 90 |     将data文件夹下csv文件导入neo4j数据库。注意这里我放上了我的服务器，可以直接用。你也可以用data2neo4j.py将数据导入到自己的本地服务器，并在question_template.py修改地址即可。 91 | 92 |     import文件夹是neo4j默认的数据导入文件夹，所以首先要将data文件夹下所有csv文件拷贝到neo4j数据库的根目录import文件夹下，没有则先创建import文件夹，然后运行此程序。 93 | 94 | #### question_classification.py 95 | 96 |     对问题进行分类 97 | 98 | #### question_template.py 99 | 100 |     连接数据库，生成查询语句，返回结果 101 | 102 | #### process_question.py 103 | 104 |     分类并回答问题 105 | 106 | #### static文件夹 107 | 108 |     放的是关于前端显示的静态文件 109 | 110 | ## 评价 111 | 112 | 随机生成了30个问题，发现问题分类的准确率在90%左右，可能是因为训练样本较少的缘故。然后问题回答的准确取决于数据库中有无数据，如果分类正确而且数据库中有相关数据，基本都能正常返回答案。后续工作需要增加问题分类的训练样本和补充数据库资源.... 113 | 114 | 115 | 116 | ## 附录 117 | 1.词性标注说明 118 | 119 | ```text 120 | n　　　普通名词 121 | nt　 　时间名词 122 | nd　 　方位名词 123 | nl　 　处所名词 124 | nh　 　人名 125 | nhf　　姓 126 | nhs　　名 127 | ns　 　地名 128 | nn 　　族名 129 | ni 　　机构名 130 | nz 　　其他专名 131 | v　　 动词 132 | vd　　趋向动词 133 | vl　　联系动词 134 | vu　　能愿动词 135 | a　 　形容词 136 | f　 　区别词 137 | m　 　数词　　 138 | q　 　量词 139 | d　 　副词 140 | r　 　代词 141 | p　　 介词 142 | c　 　连词 143 | u　　 助词 144 | e　 　叹词 145 | o　 　拟声词 146 | i　 　习用语 147 | j　　 缩略语 148 | h　　 前接成分 149 | k　　 后接成分 150 | g　 　语素字 151 | x　 　非语素字 152 | w　 　标点符号 153 | ws　　非汉字字符串 154 | wu　　其他未知的符号 155 | ``` 156 | 157 | 2.命名实体说明（采用BIO标记方式） 158 | 159 | ```text 160 | B-PER、I-PER 人名 161 | B-LOC、I-LOC 地名 162 | B-ORG、I-ORG 机构名 163 | ``` 164 | -------------------------------------------------------------------------------- /process_question.py: -------------------------------------------------------------------------------- 1 | #-*- coding: UTF-8 -*- 2 | ''' 3 | 接收原始问题 4 | 对原始问题进行分词、词性标注等处理 5 | 对问题进行抽象 6 | ''' 7 | 8 | import jieba.posseg 9 | import re 10 | from question_classification import Question_classify 11 | from question_template import QuestionTemplate 12 | import sys, os 13 | 14 | # Disable 15 | def blockPrint(): 16 | sys.stdout = open(os.devnull, 'w') 17 | # Restore 18 | def enablePrint(): 19 | sys.stdout = sys.__stdout__ 20 | # blockPrint() 21 | # enablePrint() 22 | 23 | class Question(): 24 | def __init__(self): 25 | # 初始化相关设置：读取词汇表，训练分类器，连接数据库 26 | # 训练分类器 27 | self.classify_model=Question_classify() 28 | # 读取问题模板 29 | with(open("./questions/question_classification.txt","r",encoding="utf-8")) as f: 30 | question_mode_list=f.readlines() 31 | self.question_mode_dict={} 32 | for one_mode in question_mode_list: 33 | # 读取一行 34 | mode_id,mode_str=str(one_mode).strip().split(":") 35 | # 处理一行，并存入 36 | self.question_mode_dict[int(mode_id)]=str(mode_str).strip() 37 | # 创建问题模板对象 38 | self.questiontemplate=QuestionTemplate() 39 | 40 | def question_process(self,question): 41 | # 接收问题 42 | self.raw_question=str(question).strip() 43 | # 对问题进行词性标注 44 | self.pos_quesiton=self.question_posseg() 45 | # 得到问题的模板 46 | self.question_template_id_str=self.get_question_template() 47 | # 查询图数据库,得到答案 48 | self.answer=self.query_template() 49 | return(self.answer) 50 | 51 | def question_posseg(self): 52 | jieba.load_userdict("./questions/userdict3.txt") 53 | clean_question = re.sub("[\s+\.\!\/_,$%^*(+\"\')]+|[+——()?【】“”！，。？、~@#￥%……&*（）]+","",self.raw_question) 54 | self.clean_question=clean_question 55 | question_seged=jieba.posseg.cut(str(clean_question)) 56 | result=[] 57 | question_word, question_flag = [], [] 58 | for w in question_seged: 59 | temp_word=f"{w.word}/{w.flag}" 60 | result.append(temp_word) 61 | # 预处理问题 62 | word, flag = w.word,w.flag 63 | question_word.append(str(word).strip()) 64 | question_flag.append(str(flag).strip()) 65 | assert len(question_flag) == len(question_word) 66 | self.question_word = question_word 67 | self.question_flag = question_flag 68 | print(result) 69 | return result 70 | 71 | def get_question_template(self): 72 | # 抽象问题 73 | for item in ['nr','nm','ng']: 74 | while (item in self.question_flag): 75 | ix=self.question_flag.index(item) 76 | self.question_word[ix]=item 77 | self.question_flag[ix]=item+"ed" 78 | # 将问题转化字符串 79 | str_question="".join(self.question_word) 80 | print("抽象问题为：",str_question) 81 | # 通过分类器获取问题模板编号 82 | question_template_num=self.classify_model.predict(str_question) 83 | print("使用模板编号：",question_template_num) 84 | question_template=self.question_mode_dict[question_template_num] 85 | print("问题模板：",question_template) 86 | question_template_id_str=str(question_template_num)+"\t"+question_template 87 | return question_template_id_str 88 | 89 | 90 | # 根据问题模板的具体类容，构造cql语句，并查询 91 | def query_template(self): 92 | # 调用问题模板类中的获取答案的方法 93 | try: 94 | answer=self.questiontemplate.get_question_answer(self.pos_quesiton,self.question_template_id_str) 95 | except: 96 | answer="我也不知道啊！" 97 | return answer 98 | -------------------------------------------------------------------------------- /question_template.py: -------------------------------------------------------------------------------- 1 | #-*- coding: UTF-8 -*- 2 | #连接数据库，生成查询语句，返回结果 3 | 4 | import re 5 | from py2neo import Graph 6 | 7 | class Query(): 8 | def __init__(self): 9 | #这里暂时使用的是我的服务器数据库，你也可以搭建自己的本地数据库 10 | self.graph=Graph("http://104.224.145.185:7474", username="neo4j",password="123456") 11 | # 运行cql语句 12 | def run(self,cql): 13 | find_rela = self.graph.run(cql) 14 | return find_rela 15 | 16 | 17 | class QuestionTemplate(): 18 | def __init__(self): 19 | self.q_template_dict={ 20 | 0:self.get_movie_rating, 21 | 1:self.get_movie_releasedate, 22 | 2:self.get_movie_type, 23 | 3:self.get_movie_introduction, 24 | 4:self.get_movie_actor_list, 25 | 5:self.get_actor_info, 26 | 6:self.get_actor_act_type_movie, 27 | 7:self.get_actor_act_movie_list, 28 | 8:self.get_movie_rating_bigger, 29 | 9:self.get_movie_rating_smaller, 30 | 10:self.get_actor_movie_type, 31 | 11:self.get_cooperation_movie_list, 32 | 12:self.get_actor_movie_num, 33 | 13:self.get_actor_birthday 34 | } 35 | 36 | # 连接数据库 37 | self.graph = Query() 38 | 39 | def get_question_answer(self,question,template): 40 | # 如果问题模板的格式不正确则结束 41 | assert len(str(template).strip().split("\t"))==2 42 | template_id,template_str=int(str(template).strip().split("\t")[0]),str(template).strip().split("\t")[1] 43 | self.template_id=template_id 44 | self.template_str2list=str(template_str).split() 45 | 46 | # 预处理问题 47 | question_word,question_flag=[],[] 48 | for one in question: 49 | word, flag = one.split("/") 50 | question_word.append(str(word).strip()) 51 | question_flag.append(str(flag).strip()) 52 | assert len(question_flag)==len(question_word) 53 | self.question_word=question_word 54 | self.question_flag=question_flag 55 | self.raw_question=question 56 | # 根据问题模板来做对应的处理，获取答案 57 | answer=self.q_template_dict[template_id]() 58 | return answer 59 | 60 | # 获取电影名字 61 | def get_movie_name(self): 62 | ## 获取nm在原问题中的下标 63 | tag_index = self.question_flag.index("nm") 64 | ## 获取电影名称 65 | movie_name = self.question_word[tag_index] 66 | return movie_name 67 | def get_name(self,type_str): 68 | name_count=self.question_flag.count(type_str) 69 | if name_count==1: 70 | ## 获取nm在原问题中的下标 71 | tag_index = self.question_flag.index(type_str) 72 | ## 获取电影名称 73 | name = self.question_word[tag_index] 74 | return name 75 | else: 76 | result_list=[] 77 | for i,flag in enumerate(self.question_flag): 78 | if flag==str(type_str): 79 | result_list.append(self.question_word[i]) 80 | return result_list 81 | 82 | def get_num_x(self): 83 | x = re.sub(r'\D', "", "".join(self.question_word)) 84 | return x 85 | # 0:nm 评分 86 | def get_movie_rating(self): 87 | # 获取电影名称，这个是在原问题中抽取的 88 | movie_name=self.get_movie_name() 89 | cql = f"match (m:Movie)-[]->() where m.title='{movie_name}' return m.rating" 90 | print(cql) 91 | answer = self.graph.run(cql) 92 | answer = round(list(answer)[0][0],2) 93 | final_answer=movie_name+"电影评分为"+str(answer)+"分！" 94 | return final_answer 95 | # 1:nm 上映时间 96 | def get_movie_releasedate(self): 97 | movie_name = self.get_movie_name() 98 | cql = f"match(m:Movie)-[]->() where m.title='{movie_name}' return m.releasedate" 99 | print(cql) 100 | answer = self.graph.run(cql) 101 | answer = list(answer)[0][0] 102 | final_answer = movie_name + "的上映时间是" + str(answer) + "！" 103 | return final_answer 104 | # 2:nm 类型 105 | def get_movie_type(self): 106 | movie_name = self.get_movie_name() 107 | cql = f"match(m:Movie)-[r:is]->(b) where m.title='{movie_name}' return b.name" 108 | print(cql) 109 | answer = self.graph.run(cql) 110 | answer_list=list(answer) 111 | answers = [] 112 | for ans in answer_list: 113 | answers.append(str(ans[0])) 114 | answers="、".join(answers) 115 | final_answer = movie_name + "是" + answers + "等类型的电影！" 116 | return final_answer 117 | # 3:nm 简介 118 | def get_movie_introduction(self): 119 | movie_name = self.get_movie_name() 120 | cql = f"match(m:Movie)-[]->() where m.title='{movie_name}' return m.introduction" 121 | print(cql) 122 | answer = self.graph.run(cql) 123 | final_answer = movie_name + "主要讲述了" + str(list(answer)[0][0]) + "！" 124 | return final_answer 125 | # 4:nm 演员列表 126 | def get_movie_actor_list(self): 127 | movie_name=self.get_movie_name() 128 | cql = f"match(n:Person)-[r:actedin]->(m:Movie) where m.title='{movie_name}' return n.name" 129 | print(cql) 130 | answer = self.graph.run(cql) 131 | answer_list = list(answer) 132 | answers = [] 133 | for ans in answer_list: 134 | answers.append(str(ans[0])) 135 | answers = "、".join(answers) 136 | final_answer = movie_name + "由" + answers + "等演员主演！" 137 | return final_answer 138 | # 5:nnt 介绍 139 | def get_actor_info(self): 140 | actor_name = self.get_name('nr') 141 | cql = f"match(n:Person)-[]->() where n.name='{actor_name}' return n.biography" 142 | print(cql) 143 | answer = self.graph.run(cql) 144 | final_answer = list(answer)[0][0] 145 | return final_answer 146 | # 6:nnt ng 电影作品 147 | def get_actor_act_type_movie(self): 148 | actor_name = self.get_name("nr") 149 | type=self.get_name("ng") 150 | # 查询电影名称 151 | cql = f"match(n:Person)-[]->(m:Movie) where n.name='{actor_name}' return m.title" 152 | print(cql) 153 | movie_name_list = list(self.graph.run(cql)) 154 | #print(movie_name_list) 155 | # 查询类型 156 | result = [] 157 | for movie_name in movie_name_list: 158 | movie_name = movie_name[0].strip() 159 | try: 160 | cql = f"match(m:Movie)-[r:is]->(t) where m.title='{movie_name}' return t.name" 161 | #print(cql) 162 | temp_type = [] 163 | temp = list(self.graph.run(cql)) 164 | for t in temp: 165 | temp_type.append(t[0]) 166 | #print(temp_type) 167 | if len(temp_type) == 0: 168 | continue 169 | if type in temp_type: 170 | result.append(movie_name) 171 | except: 172 | continue 173 | #print(result) 174 | answers = "、".join(result) 175 | final_answer = actor_name + "演过的" + type + "电影有:\n" + answers + "。" 176 | return final_answer 177 | 178 | 179 | # 7:nnt 电影作品 180 | def get_actor_act_movie_list(self): 181 | actor_name = self.get_name("nr") 182 | answers=self.get_actorname_movie_list(actor_name) 183 | answer_list = "、".join(answers) 184 | final_answer = actor_name + "演过" + answer_list + "等电影！" 185 | return final_answer 186 | def get_actorname_movie_list(self,actorname): 187 | # 查询电影名称 188 | cql = f"match(n:Person)-[]->(m:Movie) where n.name='{actorname}' return m.title" 189 | print(cql) 190 | answer = self.graph.run(cql) 191 | answer_list = list(answer) 192 | answers = [] 193 | for ans in answer_list: 194 | answers.append(str(ans[0])) 195 | return answers 196 | 197 | # 8:nnt 参演评分 大于 x 198 | def get_movie_rating_bigger(self): 199 | actor_name=self.get_name('nr') 200 | x=self.get_num_x() 201 | cql = f"match(n:Person)-[r:actedin]->(m:Movie) where n.name='{actor_name}' and m.rating>={x} return m.title" 202 | print(cql) 203 | answer = self.graph.run(cql) 204 | answer_list = list(answer) 205 | answers = [] 206 | for ans in answer_list: 207 | answers.append(str(ans[0])) 208 | answer_list = "、".join(answers) 209 | final_answer=actor_name+"演的电影评分大于"+x+"分的有"+answer_list+"等！" 210 | return final_answer 211 | 212 | # 9:nnt 参演评分 小于 x 213 | def get_movie_rating_smaller(self): 214 | actor_name = self.get_name('nr') 215 | x = self.get_num_x() 216 | cql = f"match(n:Person)-[r:actedin]->(m:Movie) where n.name='{actor_name}' and m.rating<{x} return m.title" 217 | print(cql) 218 | answer = self.graph.run(cql) 219 | answer_list = list(answer) 220 | answers = [] 221 | for ans in answer_list: 222 | answers.append(str(ans[0])) 223 | answer_list = "、".join(answers) 224 | final_answer = actor_name + "演的电影评分小于" + x + "分的有" + answer_list + "等！" 225 | return final_answer 226 | 227 | # 10:nnt 出演过哪些类型的电影 228 | def get_actor_movie_type(self): 229 | actor_name = self.get_name("nr") 230 | # 查询电影名称 231 | cql = f"match(n:Person)-[]->(m:Movie) where n.name='{actor_name}' return m.title" 232 | print(cql) 233 | movie_name_list = list(self.graph.run(cql)) 234 | # 查询类型 235 | #print(movie_name_list) 236 | result = set('') 237 | for movie_name in movie_name_list: 238 | movie_name = movie_name[0].strip() 239 | try: 240 | cql = f"match(m:Movie)-[r:is]->(t) where m.title='{movie_name}' return t.name" 241 | # print(cql) 242 | temp_type = [] 243 | temp = list(self.graph.run(cql)) 244 | for t in temp: 245 | result.add(t[0]) 246 | if len(temp_type) == 0: 247 | continue 248 | #result.add(temp_type) 249 | except: 250 | continue 251 | answers = "、".join(result) 252 | final_answer = actor_name + "演过的电影有" + answers + "等类型。" 253 | return final_answer 254 | 255 | 256 | # 11: 演员A和演员B合作了哪些电影 257 | def get_cooperation_movie_list(self): 258 | # 获取演员名字 259 | actor_name_list=self.get_name('nr') 260 | movie_list={} 261 | for i,actor_name in enumerate(actor_name_list): 262 | answer_list=self.get_actorname_movie_list(actor_name) 263 | movie_list[i]=answer_list 264 | result_list=list(set(movie_list[0]).intersection(set(movie_list[1]))) 265 | #print(result_list) 266 | answer="、".join(result_list) 267 | final_answer=actor_name_list[0]+"和"+actor_name_list[1]+"一起演过的电影主要有"+answer+"!" 268 | return final_answer 269 | 270 | # 12: nnt 一共演过多少部电影 271 | def get_actor_movie_num(self): 272 | actor_name=self.get_name("nr") 273 | answer_list=self.get_actorname_movie_list(actor_name) 274 | movie_num=len(set(answer_list)) 275 | answer=movie_num 276 | final_answer=actor_name+"演过"+str(answer)+"部电影!" 277 | return final_answer 278 | 279 | # 13: nnt 出生日期 280 | def get_actor_birthday(self): 281 | actor_name = self.get_name('nr') 282 | cql = f"match(n:Person)-[]->() where n.name='{actor_name}' return n.birth" 283 | print(cql) 284 | answer = self.graph.run(cql) 285 | #print(list(answer)[0][0]) 286 | final_answer = actor_name+"的生日是"+list(answer)[0][0]+"。" 287 | return final_answer 288 | -------------------------------------------------------------------------------- /questions/userdict3.txt: -------------------------------------------------------------------------------- 1 | Forrest Gump 15 nm 2 | Kill Bill: Vol. 1 15 nm 3 | 英雄 15 nm 4 | Miami Vice 15 nm 5 | Indiana Jones and the Temple of Doom 15 nm 6 | 卧虎藏龙 15 nm 7 | Pirates of the Caribbean: At World's End 15 nm 8 | Kill Bill: Vol. 2 15 nm 9 | The Matrix Reloaded 15 nm 10 | The Matrix Revolutions 15 nm 11 | Harry Potter and the Chamber of Secrets 15 nm 12 | Harry Potter and the Prisoner of Azkaban 15 nm 13 | Harry Potter and the Goblet of Fire 15 nm 14 | Harry Potter and the Order of the Phoenix 15 nm 15 | The Last Emperor 15 nm 16 | Harry Potter and the Half-Blood Prince 15 nm 17 | 花样年华 15 nm 18 | 2046 15 nm 19 | Lethal Weapon 4 15 nm 20 | Hannibal Rising 15 nm 21 | TMNT 15 nm 22 | 무사 15 nm 23 | Anna and the King 15 nm 24 | 满城尽带黄金甲 15 nm 25 | Teenage Mutant Ninja Turtles III 15 nm 26 | The Forbidden Kingdom 15 nm 27 | The Mummy: Tomb of the Dragon Emperor 15 nm 28 | Memoirs of a Geisha 15 nm 29 | Shakespeare in Love 15 nm 30 | Lara Croft Tomb Raider: The Cradle of Life 15 nm 31 | Wu Ji 15 nm 32 | Romeo Must Die 15 nm 33 | Rush Hour 15 nm 34 | 巴尔扎克与小裁缝 15 nm 35 | 风云雄霸天下 15 nm 36 | Kiss of the Dragon 15 nm 37 | Stardust 15 nm 38 | The Long Run 15 nm 39 | 暗战 15 nm 40 | 最佳拍档 15 nm 41 | Zuijia paidang daxian shentong 15 nm 42 | Zuijia paidang zhi nuhuang miling 15 nm 43 | Zuijia paidang zhi qianli jiu chaipo 15 nm 44 | 新最佳拍档 15 nm 45 | The Transporter 15 nm 46 | 色‧戒 15 nm 47 | Mimic 15 nm 48 | Rush Hour 3 15 nm 49 | Rush Hour 2 15 nm 50 | Shanghai Knights 15 nm 51 | Australia 15 nm 52 | 文雀 15 nm 53 | 霍元甲 15 nm 54 | Samsara 15 nm 55 | The Gods Must Be Crazy 15 nm 56 | A Cock and Bull Story 15 nm 57 | Shanghai Noon 15 nm 58 | 我是谁 15 nm 59 | 一半海水一半火焰 15 nm 60 | 倩女幽魂III：道道道 15 nm 61 | 倩女幽魂II人间道 15 nm 62 | DOA: Dead or Alive 15 nm 63 | 警察故事 15 nm 64 | 饺子 15 nm 65 | 警察故事4之简单任务 15 nm 66 | The Borrowers 15 nm 67 | The Corruptor 15 nm 68 | 黑侠 15 nm 69 | Enter the Dragon 15 nm 70 | 功夫 15 nm 71 | Charlie's Angels: Full Throttle 15 nm 72 | Kung Fu Panda 15 nm 73 | 十面埋伏 15 nm 74 | 全职杀手 15 nm 75 | Double Impact 15 nm 76 | Koroshiya 1 15 nm 77 | Unleashed 15 nm 78 | High Heels and Low Lifes 15 nm 79 | 福星高照 15 nm 80 | 小白龙情海翻波 15 nm 81 | Around the World in 80 Days 15 nm 82 | Kickboxer 15 nm 83 | Chin Kei Bin 2 - Fa Tou Tai Kam 15 nm 84 | 韩城攻略 15 nm 85 | Shao Lin Si 15 nm 86 | 霹雳火 15 nm 87 | 荆轲刺秦王 15 nm 88 | 大红灯笼高高挂 15 nm 89 | War 15 nm 90 | 饮食男女 15 nm 91 | The Medallion 15 nm 92 | Sat sau ji wong 15 nm 93 | 黄飞鸿 15 nm 94 | 黄飞鸿之二男儿当自强 15 nm 95 | 黄飞鸿之三狮王争霸 15 nm 96 | 黄飞鸿之西域雄狮 15 nm 97 | 一个好人 15 nm 98 | Cradle 2 the Grave 15 nm 99 | Mulan 15 nm 100 | 七剑 15 nm 101 | 警察故事续集 15 nm 102 | The Tuxedo 15 nm 103 | 无间道 15 nm 104 | The One 15 nm 105 | 喋血双雄 15 nm 106 | 倚天屠龙记之魔教教主 15 nm 107 | 赤裸特工 15 nm 108 | 琉璃樽 15 nm 109 | 龙兄虎弟 15 nm 110 | 飞鹰计划 15 nm 111 | L'Amant 15 nm 112 | 霸王别姬 15 nm 113 | Year of the Dragon 15 nm 114 | 重庆森林 15 nm 115 | 警察故事 III：超级警察 15 nm 116 | 太极张三丰 15 nm 117 | 城市猎人 15 nm 118 | 快餐车 15 nm 119 | 堕落天使 15 nm 120 | 醉拳 15 nm 121 | The Cannonball Run 15 nm 122 | 8 ½ Women 15 nm 123 | 英雄本色 15 nm 124 | 盲井 15 nm 125 | 蛇形刁手 15 nm 126 | 千禧曼波 15 nm 127 | 最好的时光 15 nm 128 | 师弟出马 15 nm 129 | 新警察故事 15 nm 130 | 无间道II 15 nm 131 | Shen hua 15 nm 132 | Bloodsport 15 nm 133 | The Replacement Killers 15 nm 134 | 精武门 15 nm 135 | 少林足球 15 nm 136 | 辣手神探 15 nm 137 | Bulletproof Monk 15 nm 138 | 少林卅六房 15 nm 139 | 特务迷城 15 nm 140 | Kung Pow: Enter the Fist 15 nm 141 | 牒血街头 15 nm 142 | The Gods Must Be Crazy II 15 nm 143 | Cannonball Run II 15 nm 144 | Fu Zi 15 nm 145 | 醉拳二 15 nm 146 | Highlander: Endgame 15 nm 147 | Монгол 15 nm 148 | 我的父亲母亲 15 nm 149 | Chi bi 15 nm 150 | 荡寇 15 nm 151 | Harry Potter and the Deathly Hallows: Part 1 15 nm 152 | Harry Potter and the Deathly Hallows: Part 2 15 nm 153 | 唐山大兄 15 nm 154 | Dai si gin 15 nm 155 | New York, I Love You 15 nm 156 | 少年黄飞鸿之铁马骝 15 nm 157 | Dak ging san yan lui 15 nm 158 | 杀破狼 15 nm 159 | 西游记第壹佰零壹回之月光宝盒 15 nm 160 | A Room with a View 15 nm 161 | 鬼域 15 nm 162 | 黄石的孩子 15 nm 163 | Wu du 15 nm 164 | Jin bei tong 15 nm 165 | 豪侠 15 nm 166 | 长江七号 15 nm 167 | 放‧逐 15 nm 168 | Race to Witch Mountain 15 nm 169 | 神探 15 nm 170 | Ji jie hao / Assembly 15 nm 171 | Dragonball Evolution 15 nm 172 | Wake of Death 15 nm 173 | The Painted Veil 15 nm 174 | The Red Violin 15 nm 175 | 无间道III: 终极无间 15 nm 176 | 投名状 15 nm 177 | Ye yan 15 nm 178 | 三国之见龙卸甲 15 nm 179 | 江山美人 15 nm 180 | The Matrix Revisited 15 nm 181 | Anita and Me 15 nm 182 | Boarding Gate 15 nm 183 | 叶问 15 nm 184 | Tian di ying xiong 15 nm 185 | 墨攻 15 nm 186 | 狗咬狗 15 nm 187 | The Guyver 15 nm 188 | 黑社会2：以和为贵 15 nm 189 | 夕阳天使 15 nm 190 | 赤壁 2 15 nm 191 | 鬼打鬼 15 nm 192 | Zhong hua ying xiong 15 nm 193 | 牯岭街少年杀人事件 15 nm 194 | 龙虎门 15 nm 195 | Bodyguard: A New Beginning 15 nm 196 | 双子神偷 15 nm 197 | 鬼马天师 15 nm 198 | Du shen 15 nm 199 | Shu shan zheng zhuan 15 nm 200 | Dragon Lord 15 nm 201 | Tau man ji D 15 nm 202 | Oh Schucks...! Here Comes UNTAG 15 nm 203 | 门徒 15 nm 204 | Wushu 15 nm 205 | 神枪手 / Sun cheung sau 15 nm 206 | Gong fu guan lan 15 nm 207 | They Wait 15 nm 208 | 颐和园 15 nm 209 | 千机变 15 nm 210 | 力王 15 nm 211 | 方世玉 15 nm 212 | Hua pi 15 nm 213 | Jing wu ying xiong 15 nm 214 | Fong Sai Yuk juk jaap 15 nm 215 | Dark Matter 15 nm 216 | 証人 15 nm 217 | 非诚勿扰 15 nm 218 | Ying hung boon sik II 15 nm 219 | 阿飞正传 15 nm 220 | 春光乍洩 15 nm 221 | He ni zai yi qi 15 nm 222 | 데이지 15 nm 223 | Horsemen 15 nm 224 | 鼠胆龙威 15 nm 225 | 新精武门 15 nm 226 | 东方不败之风云再起 15 nm 227 | Hong Xi Guan: Zhi Shao Lin wu zu 15 nm 228 | 笑傲江湖II东方不败 15 nm 229 | Zhong Nan Hai bao biao 15 nm 230 | 파이란 15 nm 231 | 夏日福星 15 nm 232 | 给爸爸的信 15 nm 233 | 黄飞鸿之铁鸡斗蜈蚣 15 nm 234 | 飞渡捲云山 15 nm 235 | 龙腾虎跃 15 nm 236 | 黑社会 15 nm 237 | Jian hua yan yu Jiang Nan 15 nm 238 | 拳精 15 nm 239 | 龙的心 15 nm 240 | 双龙会 15 nm 241 | 火烧岛 15 nm 242 | Lin Shi Rong 15 nm 243 | 龙之忍者 15 nm 244 | Liu zhi qin mo 15 nm 245 | Mang lung 15 nm 246 | 白发魔女传 15 nm 247 | Xilu xiang 15 nm 248 | Huo Yuan-Jia 15 nm 249 | 蠍子战士 15 nm 250 | 重案组 15 nm 251 | 笑傲江湖 15 nm 252 | 招半式闯江湖 15 nm 253 | 伤城 15 nm 254 | 复仇 15 nm 255 | 十八般武艺 15 nm 256 | The Big Brawl 15 nm 257 | 笑拳怪招 15 nm 258 | Mo hup leung juk 15 nm 259 | 赌神2 15 nm 260 | 男儿本色 15 nm 261 | Bo chi tung wah 15 nm 262 | 蝴蝶 15 nm 263 | Chandni Chowk To China 15 nm 264 | 新宿事件 15 nm 265 | 如来神掌 15 nm 266 | 不能说的秘密 15 nm 267 | Ha Yat Dik Mo Mo Cha 15 nm 268 | 龙行天下 15 nm 269 | Shao Lin yu Wu Dang 15 nm 270 | 南京!南京! 15 nm 271 | A计划 15 nm 272 | A计划续集 15 nm 273 | Da lao ai mei li 15 nm 274 | Ding tian li di 15 nm 275 | 十四女英豪 15 nm 276 | 조폭 마누라 2: 돌아온 전설 15 nm 277 | Fei lung mang jeung 15 nm 278 | 西游记大结局之仙履奇缘 15 nm 279 | 天下第一拳 15 nm 280 | The Man from Hong Kong 15 nm 281 | Encrypt 15 nm 282 | 洪熙官 15 nm 283 | Ga yau hei si 2009 15 nm 284 | Shôrin shôjo 15 nm 285 | โลงต่อตาย 15 nm 286 | Feng Yun Jue 15 nm 287 | Shi ying xiong chong ying xiong 15 nm 288 | Kinamand 15 nm 289 | The Spy Next Door 15 nm 290 | Ten Minutes Older: The Trumpet 15 nm 291 | Mai dou xiang dang dang 15 nm 292 | Iron And Silk 15 nm 293 | 旺角卡门 15 nm 294 | Seventh Moon 15 nm 295 | 新座头市　破れ！唐人剣 15 nm 296 | Into the Sun 15 nm 297 | Andy Lau Wonderful World Concert Tour Shanghai 2008 15 nm 298 | Gin gwai 2 15 nm 299 | 窃听风云 15 nm 300 | 伊波拉病毒 15 nm 301 | Fei chang wan mei 15 nm 302 | Kickboxer 2: The Road Back 15 nm 303 | 奇蹟 15 nm 304 | Gong fu chu shen 15 nm 305 | Joi sun ho 15 nm 306 | Irma Vep 15 nm 307 | Bai fa mo nu zhuan II 15 nm 308 | Kung Fu Killer 15 nm 309 | 笑太极 15 nm 310 | Yi ngoi 15 nm 311 | PTU 15 nm 312 | 一一 15 nm 313 | 奇谋妙计五福星 15 nm 314 | 建国大业 15 nm 315 | Wing Chun 15 nm 316 | 缘份 15 nm 317 | Duo shuai 15 nm 318 | Hung kuen dai see 15 nm 319 | 柔道龙虎榜 15 nm 320 | Bo bui gai wak 15 nm 321 | Mor gwai tin si 15 nm 322 | 鬼子来了 15 nm 323 | Long nga 15 nm 324 | 秘岸 15 nm 325 | Duo biao 15 nm 326 | 大醉侠 15 nm 327 | The Pillow Book 15 nm 328 | The Legend of the 7 Golden Vampires 15 nm 329 | Muk lau hung gwong 15 nm 330 | Hu bao long she ying 15 nm 331 | Zhui Ying 15 nm 332 | 陆阿采与黄飞鸿 15 nm 333 | Qin Song 15 nm 334 | 天涯明月刀 15 nm 335 | 赤裸羔羊 15 nm 336 | Dai noi muk taam 009 15 nm 337 | Mei shao nian zhi lian 15 nm 338 | Lan Yu 15 nm 339 | 侠盗高飞 15 nm 340 | The Expendables 15 nm 341 | 六壮士 15 nm 342 | Xin du bi dao 15 nm 343 | House of Fury 15 nm 344 | Shamo 15 nm 345 | 旺角黑夜 15 nm 346 | 群龙戏凤 15 nm 347 | 宋家皇朝 15 nm 348 | 天下无贼 15 nm 349 | 虎鹤双形 15 nm 350 | Tai-Pan 15 nm 351 | 飞虎雄心2傲气比天高 15 nm 352 | 二十四城记 15 nm 353 | Pou hark wong 15 nm 354 | Legend of the Dragonslayer Sword 15 nm 355 | Adventures of Power 15 nm 356 | 苹果 15 nm 357 | Chinese Box 15 nm 358 | 倩女幽魂 15 nm 359 | 十月围城 15 nm 360 | 麦田 15 nm 361 | 黑拳 15 nm 362 | Mao xian wang 15 nm 363 | Baiyin diguo 15 nm 364 | 活着 15 nm 365 | Ching toi 15 nm 366 | Heaven & Earth 15 nm 367 | Prisoner 701: Sasori 15 nm 368 | The Touch 15 nm 369 | 铁三角 15 nm 370 | 黑白战场 15 nm 371 | 三岔口 15 nm 372 | Bau lit do see 15 nm 373 | 大只佬 15 nm 374 | Gong yuan 2000 AD 15 nm 375 | 金燕子 15 nm 376 | 金瓶梅2 爱的奴隶 15 nm 377 | 审死官 15 nm 378 | 五郎八卦棍 15 nm 379 | Women From Mars 15 nm 380 | Feng sheng 15 nm 381 | 满清十大酷刑 15 nm 382 | 风云Ⅱ 15 nm 383 | 花木兰 15 nm 384 | Ma Yong Zhen 15 nm 385 | 摩登保镳 15 nm 386 | 硬汉 15 nm 387 | Chin Long Chuen Suet 15 nm 388 | 红番区 15 nm 389 | 龙凤斗 15 nm 390 | 쓰리, 몬스터 15 nm 391 | Jin Yi Wei 15 nm 392 | 孔子 15 nm 393 | 战·鼓 15 nm 394 | 我的最爱 15 nm 395 | 紫蝴蝶 15 nm 396 | 搏命单刀夺命抢 15 nm 397 | Mit moon 15 nm 398 | 刁手怪招 15 nm 399 | Leui ting jin ging 15 nm 400 | 龙在天涯 15 nm 401 | 金瓶梅 15 nm 402 | 决战紫禁之顚 15 nm 403 | 大兵小将 15 nm 404 | Snake and Crane Arts of Shaolin 15 nm 405 | Sing kung chok tse yee: Ngor but mai sun, ngor mai chi gung 15 nm 406 | 导火线 15 nm 407 | Luo ye gui gen 15 nm 408 | Ngo liu poh lut gau ching 15 nm 409 | Dead or Alive: Final 15 nm 410 | 极道黒社会 15 nm 411 | 十三太保 15 nm 412 | Xích lô 15 nm 413 | Hyôryû-gai 15 nm 414 | Qing feng xia 15 nm 415 | 半支烟 15 nm 416 | Blade II 15 nm 417 | One Last Dance 15 nm 418 | Die Another Day 15 nm 419 | 合气道 15 nm 420 | Hak bak do 15 nm 421 | Shao Lin xiao zi 15 nm 422 | 南北少林 15 nm 423 | Su Qi-Er 15 nm 424 | Tian mi mi 15 nm 425 | The Final Curtain 15 nm 426 | 全城热恋 15 nm 427 | 叶问2: 宗师传奇 15 nm 428 | Sham moh 15 nm 429 | Jump 15 nm 430 | 摇啊摇，摇到外婆桥 15 nm 431 | Bruce Lee: A Warrior's Journey 15 nm 432 | 大内密探零零发 15 nm 433 | 唐伯虎点秋香 15 nm 434 | オペレッタ狸御殿 15 nm 435 | Ai qing hu jiao zhuan yi 15 nm 436 | Ci Ling 15 nm 437 | Wo de tangchao xiongdi 15 nm 438 | 同门 15 nm 439 | A Serious Shock! Yes Madam! 15 nm 440 | Keep Cool 15 nm 441 | 跟踪 15 nm 442 | Invisible Waves 15 nm 443 | 江湖 15 nm 444 | 女警察 15 nm 445 | Sijie 15 nm 446 | Ouran 15 nm 447 | 铁汉柔情 15 nm 448 | 宝葫芦的秘密 15 nm 449 | Nu zi tai quan qun ying hui 15 nm 450 | 少林门 15 nm 451 | Fa qian han 15 nm 452 | 秋菊打官司 15 nm 453 | Zu: The Warriors from the Magic Mountain 15 nm 454 | 吴清源 15 nm 455 | For lung 15 nm 456 | Shanghai 15 nm 457 | 迷你特攻队 15 nm 458 | The Karate Kid 15 nm 459 | Huang cun ke zhan 15 nm 460 | 超级计划 15 nm 461 | Kickboxer 3: The Art of War 15 nm 462 | Li Xiao Long zhuan qi 15 nm 463 | All About Women 15 nm 464 | Sam hoi tsam yan 15 nm 465 | 满清十大酷刑之赤裸凌迟2 15 nm 466 | Hunting Venus 15 nm 467 | Huang jia shi jie 15 nm 468 | 蜈蚣咒 15 nm 469 | 杜拉拉升职记 15 nm 470 | 岁月神偷 15 nm 471 | 醉马骝 15 nm 472 | 刀马旦 15 nm 473 | 古惑仔之人在江湖 15 nm 474 | Eros 15 nm 475 | Clean 15 nm 476 | 皇家师姐IV直击证人 15 nm 477 | 八仙饭店之人肉叉烧饱 15 nm 478 | Di yu wu men 15 nm 479 | San De huo shang yu Chong Mi Liu 15 nm 480 | She sha shou 15 nm 481 | 原振侠与卫斯理 15 nm 482 | 杂家小子 15 nm 483 | 青蛇 15 nm 484 | Mi tao cheng shu shi 1997 15 nm 485 | Mei nui sik sung 15 nm 486 | 奇逢敌手 15 nm 487 | Lik goo lik goo dui dui pong 15 nm 488 | 撕票风云 15 nm 489 | Ninja Terminator 15 nm 490 | 女集中营 15 nm 491 | 尸妖 15 nm 492 | 乌鼠机密档案 15 nm 493 | Wu zhao shi ba fan 15 nm 494 | Zhong gui 15 nm 495 | Bin lim mai ching 15 nm 496 | 残缺 15 nm 497 | 羔羊医生 15 nm 498 | Hu meng wei long 15 nm 499 | 천사몽 15 nm 500 | 新流星蝴蝶剑 15 nm 501 | Shen Jing Dao yu Fei Tian Mao 15 nm 502 | 新龙门客栈 15 nm 503 | The Era of Vampires 15 nm 504 | 赌圣 15 nm 505 | Jing tian long hu bao 15 nm 506 | 烹尸之丧尽天良 15 nm 507 | 忍武者 15 nm 508 | Sang sei kuen chuk 15 nm 509 | 中国超人 15 nm 510 | Zhong kui niang zi 15 nm 511 | How Bruce Lee Changed the World 15 nm 512 | 东邪西毒 15 nm 513 | 少林木人巷 15 nm 514 | 少林英雄之方世玉洪熙官 15 nm 515 | Fen nu qing nian 15 nm 516 | 成龙的特技 15 nm 517 | 半生缘 15 nm 518 | Xiang ji mao yi yang fei 15 nm 519 | Lü cha 15 nm 520 | 伊莎贝拉 15 nm 521 | 中华丈夫 15 nm 522 | Lie mo qun ying 15 nm 523 | 杀手天使 15 nm 524 | 暗花 15 nm 525 | 大丈夫 15 nm 526 | 两个只能活一个 15 nm 527 | 向左走向右走 15 nm 528 | Ying hung boon sik III jik yeung ji gor 15 nm 529 | Bloodfight 15 nm 530 | 食神 15 nm 531 | 整蛊专家 15 nm 532 | 洪文定三破白莲教 15 nm 533 | 五遁忍术 15 nm 534 | 败家仔 15 nm 535 | 少林五祖 15 nm 536 | 国产凌凌漆 15 nm 537 | Fei ying 15 nm 538 | 恋爱行星 15 nm 539 | 越光宝盒 15 nm 540 | Daai sau cha ji neui 15 nm 541 | 未来警察 15 nm 542 | Wu hu tu long 15 nm 543 | 游龙戏凤 15 nm 544 | 机器侠 15 nm 545 | Ba hai hong ying 15 nm 546 | Bian zou bian chang 15 nm 547 | 雌雄双煞 15 nm 548 | 菊豆 15 nm 549 | 客途秋恨 15 nm 550 | Mei lai muk ling 15 nm 551 | Fei saa fung chung chun 15 nm 552 | 志明与春娇 15 nm 553 | Hong gao liang 15 nm 554 | 龙虎风云 15 nm 555 | 猩猩王 15 nm 556 | 黄飞鸿之五龙城歼霸 15 nm 557 | 조폭 마누라 3 15 nm 558 | Ga goh yau chin yan 15 nm 559 | 打擂台 15 nm 560 | El kárate, el Colt y el impostor 15 nm 561 | American Fusion 15 nm 562 | 高度戒备 15 nm 563 | Dao 15 nm 564 | 黑金 15 nm 565 | 瘦身男女 15 nm 566 | Attack Force Z 15 nm 567 | Dung fong saam hap 15 nm 568 | Zhong hua zhan shi 15 nm 569 | 水浒传 15 nm 570 | 剑雨 15 nm 571 | 变节 15 nm 572 | Ai de jiao yu 15 nm 573 | 侠女 15 nm 574 | 蓝风筝 15 nm 575 | 茉莉花开 15 nm 576 | 鎗王之王 15 nm 577 | Yip Man chinchyun 15 nm 578 | 全城戒备 15 nm 579 | Yeshou xingjing 15 nm 580 | 东宫西宫 15 nm 581 | 小倩 15 nm 582 | 如果·爱 15 nm 583 | 中华英雄 15 nm 584 | 三枪拍案惊奇 15 nm 585 | 画魂 15 nm 586 | 唐山大地震 15 nm 587 | 弹道 15 nm 588 | 苏乞儿 15 nm 589 | Lian ai zhong de Bao Bei 15 nm 590 | Bruce Lee: The Legend 15 nm 591 | 心中有鬼 15 nm 592 | Jieguo 15 nm 593 | Bak Ging lok yue liu 15 nm 594 | 月满轩尼诗 15 nm 595 | 双食记 15 nm 596 | Tao hua yun 15 nm 597 | Wu ren jia shi 15 nm 598 | Iron Fist Pillage 15 nm 599 | Mei Lanfang 15 nm 600 | Gaai tau saat sau 15 nm 601 | 雪儿 15 nm 602 | 最后胜利 15 nm 603 | 一代宗师 15 nm 604 | 蝶变 15 nm 605 | Shi zi mo hou shou 15 nm 606 | 鬼猛脚 15 nm 607 | Death Code: Ninja 15 nm 608 | 大小黄天霸 15 nm 609 | Bat sei ching mai 15 nm 610 | 暗战 2 15 nm 611 | Ming Ming 15 nm 612 | 天下无双 15 nm 613 | B gai waak 15 nm 614 | 百年好合 15 nm 615 | Mou han fou wut 15 nm 616 | Bad Boy特攻 15 nm 617 | Gau lung bing sat 15 nm 618 | i九一神鵰侠侣 15 nm 619 | Bi xie lan tian 15 nm 620 | Biu Che Ji Che San Chuen Suet 15 nm 621 | Ngo joh aan gin diy gwai 15 nm 622 | City Of Glass 15 nm 623 | 城市女猎人 15 nm 624 | 赤色大风暴 15 nm 625 | The Protector 15 nm 626 | Oi yue shing 15 nm 627 | La Brassiere 15 nm 628 | 安娜与武林 15 nm 629 | Chuet sik san tau 15 nm 630 | Gon chaai lit feng 15 nm 631 | 钟无艳 15 nm 632 | 孤男寡女 15 nm 633 | Chung on chi ma gun 15 nm 634 | 天堂口 15 nm 635 | Pao zhi nu peng you 15 nm 636 | Pau mui 15 nm 637 | Gwai ma kwong seung kuk 15 nm 638 | Tou shen gu zu 15 nm 639 | 大冒险家 15 nm 640 | 黑猫 15 nm 641 | 东京攻略 15 nm 642 | 戏王之王 15 nm 643 | 卫斯理蓝血人 15 nm 644 | 花旗少林 15 nm 645 | Hong tian huang jia jiang 15 nm 646 | 皇家女将 15 nm 647 | 煎酿叁宝 15 nm 648 | He yue qing ren 15 nm 649 | 皇家战士 15 nm 650 | 回魂夜 15 nm 651 | 香港奇案之强奸 15 nm 652 | 急冻奇侠 15 nm 653 | Jui oi nui yun kau muk kong 15 nm 654 | Xin long zhong hu dou 15 nm 655 | 惊天12小时 15 nm 656 | 辣手回春 15 nm 657 | Xing yuan 15 nm 658 | 流氓医生 15 nm 659 | Yat luk che 15 nm 660 | Sam dung 15 nm 661 | 有情饮水饱 15 nm 662 | 野蛮密笈 15 nm 663 | 热血最强 15 nm 664 | Sat yik gaai lui wong 15 nm 665 | 老夫子 15 nm 666 | Youling renjian 15 nm 667 | Shuang xiong 15 nm 668 | 玉观音 15 nm 669 | 算死草 15 nm 670 | 十二夜 15 nm 671 | 恋战冲绳 15 nm 672 | Yu pu tuan zhi: Tou qing bao jian 15 nm 673 | Yue doh laai yue ying hung 15 nm 674 | 瘦身 15 nm 675 | Sing gam do see 15 nm 676 | 森冤 15 nm 677 | Luen ching go gup 15 nm 678 | Sun jaat si mui 15 nm 679 | Sing yuet tung wa 15 nm 680 | Luen seung ngei dik chong 15 nm 681 | 至尊无上 15 nm 682 | Sun ying hong boon sik 15 nm 683 | 摄氏32度 15 nm 684 | Skyline Cruisers 15 nm 685 | Leaving Me, Loving You 15 nm 686 | Xun zhao Cheng Long 15 nm 687 | Shao Lin si 15 nm 688 | 飞虎雄心 15 nm 689 | 黄河绝恋 15 nm 690 | Sun zat see ze 15 nm 691 | 枪火 15 nm 692 | Here Comes Fortune 15 nm 693 | 金钱帝国 15 nm 694 | 情癫大圣 15 nm 695 | 拳神 15 nm 696 | 海上花 15 nm 697 | 童年童年 15 nm 698 | 风雨双流星 15 nm 699 | 三十六迷形拳 15 nm 700 | 成龙的传奇 15 nm 701 | 龙拳 15 nm 702 | Sing si jin jang 15 nm 703 | The Warrior's Way 15 nm 704 | 人间喜剧 15 nm 705 | Cheung Gong 7 hou: Oi dei kau 15 nm 706 | 疯猴 15 nm 707 | Tin seung yan gaan 15 nm 708 | Hot Potato 15 nm 709 | Eve and the Fire Horse 15 nm 710 | Qi Tian Ai Shang Ni Year 15 nm 711 | 荒村公寓 15 nm 712 | 我爱你 15 nm 713 | Pi li long quan 15 nm 714 | 鸡同鸭讲 15 nm 715 | Changhen Ge 15 nm 716 | 纵横四海 15 nm 717 | 美丽新世界 15 nm 718 | 7 jin gong 15 nm 719 | Shui shuo wo bu zai hu 15 nm 720 | 逃学威龙 15 nm 721 | 武状元苏乞儿 15 nm 722 | 风月 15 nm 723 | Jing Gai'er 15 nm 724 | Jing wu feng yun: Chen Zhen 15 nm 725 | xXx: Return of Xander Cage 15 nm 726 | Chu Ba 15 nm 727 | Nan Shao Lin yu bei Shao Lin 15 nm 728 | Hao xia zhuan 15 nm 729 | Xin fei hu wai chuan 15 nm 730 | 独臂刀王 15 nm 731 | 少林搭棚大师 15 nm 732 | 线人 15 nm 733 | 狄仁杰之通天帝国 15 nm 734 | Si wang ta 15 nm 735 | Prince of Jutland 15 nm 736 | 古惑仔2之猛龙过江 15 nm 737 | 古惑仔之只手遮天 15 nm 738 | 97古惑仔之战无不胜 15 nm 739 | 98古惑仔之龙争虎斗 15 nm 740 | 胜者为王 15 nm 741 | 新古惑仔之少年激斗篇 15 nm 742 | Kei tung bou deui: Tung pou 15 nm 743 | 烈火战车２ 极速传说 15 nm 744 | 古惑仔情义篇之洪兴十三妹 15 nm 745 | 魔 15 nm 746 | 一个好爸爸 15 nm 747 | Single Blog 15 nm 748 | 古惑仔激情篇洪兴大飞哥 15 nm 749 | 友情岁月之山鸡故事 15 nm 750 | 顺流逆流 15 nm 751 | Kung Fu Panda 2 15 nm 752 | Te jing xin ren lei 2 15 nm 753 | 黑侠 II 15 nm 754 | 独臂拳王大破血滴子 15 nm 755 | Nan bei zui quan 15 nm 756 | 游园惊梦 15 nm 757 | 维多利亚壹号 15 nm 758 | Shen quan da zhan kuai qiang shou 15 nm 759 | Whatever Happened to Harold Smith? 15 nm 760 | Du bei chuan wang 15 nm 761 | 悲情城市 15 nm 762 | Wind Blast 15 nm 763 | 新精武门 15 nm 764 | Nui ji za pai jun 15 nm 765 | 拍案惊奇 15 nm 766 | Top Fighter 15 nm 767 | Traces of a Dragon: Jackie Chan & His Lost Family 15 nm 768 | Xi Zang xiao zi 15 nm 769 | 魔幻厨房: 15 nm 770 | Wu ye li ren 15 nm 771 | Mini 15 nm 772 | 喋血孤城 15 nm 773 | Kung Fu Panda Holiday 15 nm 774 | Fei zhou he shang 15 nm 775 | Ma Yong Zhen 15 nm 776 | 霹雳十杰 15 nm 777 | Xian si jue 15 nm 778 | 天水围的夜与雾 15 nm 779 | Lung Fung Dim 15 nm 780 | Peace Hotel 15 nm 781 | 战神传说 15 nm 782 | Gui ma fei ren 15 nm 783 | 形影不离 15 nm 784 | 人在囧途 15 nm 785 | 男人四十 15 nm 786 | 让子弹飞 / Let the Bullets Fly 15 nm 787 | 鹿鼎记 15 nm 788 | 鹿鼎记 II : 神龙敎 15 nm 789 | Ngok nam shi kin 15 nm 790 | Fa fa ying king 15 nm 791 | Color Me Love 15 nm 792 | Shao Lin jiang shi 15 nm 793 | 太阳照常升起 15 nm 794 | Wong Fei Hung ji sei: Wong je ji fung 15 nm 795 | 百变星君 15 nm 796 | Shen qiang shou yu zhi duo xing 15 nm 797 | One Stone and Two Birds 15 nm 798 | Resort Massacre 15 nm 799 | Fai seung hung che 15 nm 800 | 夜·上海 15 nm 801 | Huang jia shi jie zhi III: Ci xiong da dao 15 nm 802 | 金鸡 15 nm 803 | 得閒炒饭 15 nm 804 | 72家租客 15 nm 805 | Jiang tou 15 nm 806 | 醉侠苏乞儿 15 nm 807 | 雀圣 15 nm 808 | 伊贺忍法帖 15 nm 809 | Ninja the Protector 15 nm 810 | Tai yang zhi zi 15 nm 811 | 破坏之王 15 nm 812 | 逃学威龙 II 15 nm 813 | 喜剧之王 15 nm 814 | Hong He 15 nm 815 | 千王之王 2000 15 nm 816 | My Name Is Fame 15 nm 817 | 监狱风云 15 nm 818 | 赌侠 III 之上海滩赌圣 15 nm 819 | 烈火战车 15 nm 820 | Li Xiao Long 15 nm 821 | Hing dai 15 nm 822 | 浑身是胆 15 nm 823 | Che si shi si 15 nm 824 | 쓰리 15 nm 825 | 独臂刀 15 nm 826 | 烂头何 15 nm 827 | 独立时代 15 nm 828 | Mang quan gui shou 15 nm 829 | 唐伯虎点秋香2之四大才子 15 nm 830 | 海洋天堂 15 nm 831 | 麻将 15 nm 832 | You xia er 15 nm 833 | 前度 EX 15 nm 834 | Ji keung hei si 2011 15 nm 835 | Rage of the Tiger 15 nm 836 | E hu kuang long 15 nm 837 | Dragon Lee Vs. The 5 Brothers 15 nm 838 | 伏击 15 nm 839 | She hao dan xin zhen jiu zhou 15 nm 840 | 猛男大贼胭脂虎 15 nm 841 | Ma tou da jue dou 15 nm 842 | Xiao lao hu 15 nm 843 | The Dark Side of My Mind 15 nm 844 | 九品芝麻官之白面包靑天 15 nm 845 | 射鵰英雄传之东成西就 15 nm 846 | 新少林寺 15 nm 847 | Sacrifice 15 nm 848 | Yan tsoi gong wu 15 nm 849 | 老鼠爱上猫 15 nm 850 | 鹰爪铁布衫 15 nm 851 | 龙的传人 15 nm 852 | 豪门夜宴 15 nm 853 | 神击大道 15 nm 854 | Sheng hua te jing zhi sang shi ren wu 15 nm 855 | 监狱风云 II : 道犯 15 nm 856 | Dong kai ji 15 nm 857 | 2002 15 nm 858 | C+ jing taam 15 nm 859 | 非诚勿扰2 15 nm 860 | Gam yee wai 15 nm 861 | Vampire Warriors 15 nm 862 | Ma ko Po lo 15 nm 863 | 想飞 15 nm 864 | 我爱夜来香 15 nm 865 | 黐线枕边人 15 nm 866 | Long feng zei zhuo zei 15 nm 867 | Shuang tong 15 nm 868 | 鬼咬鬼 15 nm 869 | 脂粉双雄 15 nm 870 | 海上传奇 15 nm 871 | Shackleton 15 nm 872 | 赌神3之少年赌神 15 nm 873 | 睹侠 15 nm 874 | 红衣喇嘛 15 nm 875 | Dong fung po 15 nm 876 | Ngo oi Heung Gong: Hoi sum man seoi 15 nm 877 | Kung Phooey 15 nm 878 | Jin doi hou haap cyun 15 nm 879 | Jie dao sha ren 15 nm 880 | Zhan shen tan 15 nm 881 | Duo hun ling 15 nm 882 | Waan ying dak gung 15 nm 883 | Da Xiao Jiang Hu 15 nm 884 | Guang Dong liang zai yu 15 nm 885 | Gong Fu Yong Chun 15 nm 886 | The Road Less Traveled 15 nm 887 | 插翅虎 15 nm 888 | 特警屠龙 15 nm 889 | Sai hak chin 15 nm 890 | 龍在江湖 15 nm 891 | 旺角监狱 15 nm 892 | Huo shao hong lian si 15 nm 893 | 再见阿郎 15 nm 894 | 刀见笑 15 nm 895 | 真心英雄 15 nm 896 | Lao shu la gui 15 nm 897 | 知法犯法 15 nm 898 | Snow Flower and the Secret Fan 15 nm 899 | Kei tung bou deui - Ging lai 15 nm 900 | Kei tung bou deui: Yan sing 15 nm 901 | Kei tung bou deui: Juet lou 15 nm 902 | Kei tung bou deui: Fo pun 15 nm 903 | AV 15 nm 904 | Wu du tian luo 15 nm 905 | 至尊无上II永霸天下 15 nm 906 | 螳螂 15 nm 907 | Guangdong shi hu xing yi wu xi 15 nm 908 | 2 Young 15 nm 909 | 神奇侠侣 15 nm 910 | 富贵列车 15 nm 911 | Looper 15 nm 912 | The Shaolin Drunken Monk 15 nm 913 | 家有囍事 15 nm 914 | Meng Bo 15 nm 915 | Tau chut 15 nm 916 | 雀圣2自摸天后 15 nm 917 | 呖咕呖咕新年财 15 nm 918 | Tie qi men 15 nm 919 | Sam chong Siu Lam 15 nm 920 | Dancing Without You 15 nm 921 | 出埃及记 15 nm 922 | Lover's Discourse 15 nm 923 | Hau bei tim sum 15 nm 924 | Fit Lover 15 nm 925 | Liao zhai yan tan 15 nm 926 | Fo zhang luo han quan 15 nm 927 | 离别钧 15 nm 928 | Siu nin a Fu 15 nm 929 | Boon chui yan gaan 15 nm 930 | Fa tin hei si 2010 15 nm 931 | He xing dao shou tang lang tui 15 nm 932 | 周渔的火车 15 nm 933 | 精装追女仔2004 15 nm 934 | 忘不了 15 nm 935 | 流氓英雄 15 nm 936 | Xue di zi 15 nm 937 | 大丈夫2 15 nm 938 | 神偷谍影 15 nm 939 | Oi ching baak min baau 15 nm 940 | 再说一次我爱你 15 nm 941 | 2004新紮师兄 15 nm 942 | Long hu dou 15 nm 943 | 童梦奇缘 15 nm 944 | 太极拳 15 nm 945 | 我知女人心 15 nm 946 | Guan yun chang 15 nm 947 | 最佳福星 15 nm 948 | Return of the Lucky Stars 15 nm 949 | 五福星撞鬼 15 nm 950 | Wan choi ng fuk sing 15 nm 951 | 观音山 15 nm 952 | 决战刹马镇 15 nm 953 | Jie shi ying xiong 15 nm 954 | Yao hun 15 nm 955 | Moh din tiu lung 15 nm 956 | 日照重庆 15 nm 957 | 上海滩十三太保 15 nm 958 | 笑林小子2：新乌龙院 15 nm 959 | 超级学校霸王 15 nm 960 | 秋天的童话 15 nm 961 | 97 ga yau hei si 15 nm 962 | 太极气功 15 nm 963 | 功夫小子 15 nm 964 | 大师 15 nm 965 | Two Toothless Tigers 15 nm 966 | 怪兽学园 15 nm 967 | 神勇双响炮续集 15 nm 968 | 陆小凤之绣花大盗 15 nm 969 | 勇者无惧 15 nm 970 | 鬼画符 15 nm 971 | 龙虎会风云 15 nm 972 | Ling qi bi ren 15 nm 973 | Ying Wang 15 nm 974 | Sheng si dou 15 nm 975 | My Family 15 nm 976 | 赞先生与找钱华 15 nm 977 | 女机械人 15 nm 978 | 洪拳与咏春 15 nm 979 | Ci Ma 15 nm 980 | Xue fu men 15 nm 981 | Qi xia wu yi zhi wu shu nao dong jing 15 nm 982 | The Spirit of the Sword 15 nm 983 | Jackie Chan: Fast, Funny and Furious 15 nm 984 | Ying zi shen bian 15 nm 985 | Yan niang 15 nm 986 | Tough Beauty and the Sloppy Slop 15 nm 987 | Augustin, roi du kung-fu 15 nm 988 | 大旗英雄传 15 nm 989 | Ri jie 15 nm 990 | 圆月弯刀 15 nm 991 | Yi tian tu long ji da jie ju 15 nm 992 | Ren pi deng long 15 nm 993 | 白玉老虎 15 nm 994 | 武馆 15 nm 995 | 合家欢 15 nm 996 | 孔雀王朝 15 nm 997 | Bian cheng san xia 15 nm 998 | 黄飞鸿少林拳 15 nm 999 | Fei yan jin dao 15 nm 1000 | 香港也疯狂 15 nm 1001 | 巩俐 15 nr 1002 | 乔宏 15 nr 1003 | 李连杰 15 nr 1004 | 梁朝伟 15 nr 1005 | 张曼玉 15 nr 1006 | 章子怡 15 nr 1007 | 甄子丹 15 nr 1008 | 周润发 15 nr 1009 | 鲍德熹 15 nr 1010 | 曾江 15 nr 1011 | 吴宇森 15 nr 1012 | 张耀扬 15 nr 1013 | 成龙 15 nr 1014 | 袁和平 15 nr 1015 | 任达华 15 nr 1016 | 陈凯歌 15 nr 1017 | 张柏芝 15 nr 1018 | 刘烨 15 nr 1019 | 王文隽 15 nr 1020 | 郭富城 15 nr 1021 | 杨恭如 15 nr 1022 | 舒淇 15 nr 1023 | 方中信 15 nr 1024 | 杜琪峰 15 nr 1025 | 张学友 15 nr 1026 | 刘德华 15 nr 1027 | 林雪 15 nr 1028 | 曾志伟 15 nr 1029 | 许冠杰 15 nr 1030 | 林子祥 15 nr 1031 | 刘家良 15 nr 1032 | 陈雅伦 15 nr 1033 | 李修贤 15 nr 1034 | 黄锦燊 15 nr 1035 | 潘恒生 15 nr 1036 | 林熙蕾 15 nr 1037 | 锺丽缇 15 nr 1038 | 黄霑 15 nr 1039 | 林青霞 15 nr 1040 | 梁家辉 15 nr 1041 | 周星驰 15 nr 1042 | 元华 15 nr 1043 | 莫文蔚 15 nr 1044 | 洪金宝 15 nr 1045 | 黄炳耀 15 nr 1046 | 吴耀汉 15 nr 1047 | 胡慧中 15 nr 1048 | 林正英 15 nr 1049 | 吴镇宇 15 nr 1050 | 任贤齐 15 nr 1051 | 陈国新 15 nr 1052 | 袁咏仪 15 nr 1053 | 谷德昭 15 nr 1054 | 梁咏琪 15 nr 1055 | 姜大卫 15 nr 1056 | 关之琳 15 nr 1057 | 莫少聪 15 nr 1058 | 黄秋生 15 nr 1059 | 黎明 15 nr 1060 | 张敏 15 nr 1061 | 邱淑贞 15 nr 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鲍汉琳 15 nr 1122 | 沈殿霞 15 nr 1123 | 郭晓冬 15 nr 1124 | 刘以达 15 nr 1125 | 李力持 15 nr 1126 | 苗圃 15 nr 1127 | 元秋 15 nr 1128 | 成奎安 15 nr 1129 | 西瓜刨 15 nr 1130 | 吴辰君 15 nr 1131 | 于荣光 15 nr 1132 | 田丰 15 nr 1133 | 李美凤 15 nr 1134 | 吴启华 15 nr 1135 | 刘天兰 15 nr 1136 | 周海媚 15 nr 1137 | 徐帆 15 nr 1138 | 刘宝贤 15 nr 1139 | 柯俊雄 15 nr 1140 | 午马 15 nr 1141 | 叶进 15 nr 1142 | 龚蓓苾 15 nr 1143 | 张智霖 15 nr 1144 | 周慧敏 15 nr 1145 | 梁曼仪 15 nr 1146 | 钱嘉乐 15 nr 1147 | 锺镇涛 15 nr 1148 | 龙方 15 nr 1149 | 李蕙敏 15 nr 1150 | 陈法蓉 15 nr 1151 | 锺景辉 15 nr 1152 | 郑裕玲 15 nr 1153 | 梁家仁 15 nr 1154 | 杨丽菁 15 nr 1155 | 谷峰 15 nr 1156 | 周文健 15 nr 1157 | 卢冠廷 15 nr 1158 | 楼南光 15 nr 1159 | 任世官 15 nr 1160 | 李丽丽 15 nr 1161 | 刘家辉 15 nr 1162 | 黄百鸣 15 nr 1163 | 赵雅芝 15 nr 1164 | 王伍福 15 nr 1165 | 张国立 15 nr 1166 | 王学兵 15 nr 1167 | 林子聪 15 nr 1168 | 鬼媾人 15 nr 1169 | 陈豪 15 nr 1170 | 叶蕴仪 15 nr 1171 | 陈加玲 15 nr 1172 | 唐国强 15 nr 1173 | 胡枫 15 nr 1174 | 何东 15 nr 1175 | 叶荣祖 15 nr 1176 | 袁洁莹 15 nr 1177 | 王羽 15 nr 1178 | 陈晓东 15 nr 1179 | 刘劲 15 nr 1180 | 秦沛 15 nr 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