From 69303312ed9d4500dffebb9099b5f5f0e92809eb Mon Sep 17 00:00:00 2001 From: liu huanyong Date: Fri, 5 Oct 2018 17:20:22 +0800 Subject: [PATCH] =?UTF-8?q?=E5=AE=8C=E6=88=90=E7=9F=A5=E8=AF=86=E6=9F=A5?= =?UTF-8?q?=E8=AF=A2?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- README.md | 12 +- __pycache__/answer_search.cpython-36.pyc | Bin 855 -> 6194 bytes .../question_classifier.cpython-36.pyc | Bin 8402 -> 8462 bytes __pycache__/question_parser.cpython-36.pyc | Bin 6984 -> 7241 bytes answer_search.py | 120 +++++++++++++++++- chatbot_graph.py | 21 +-- dict/deny.txt | 4 + img/chat1.png | Bin 0 -> 576113 bytes img/chat2.png | Bin 0 -> 566775 bytes question_classifier.py | 4 +- question_parser.py | 16 ++- 11 files changed, 151 insertions(+), 26 deletions(-) create mode 100644 img/chat1.png create mode 100644 img/chat2.png diff --git a/README.md b/README.md index 24a34d4..08b3346 100644 --- a/README.md +++ b/README.md @@ -10,6 +10,17 @@ self-implement of disease centered Medical graph from zero to full and sever as 1) 基于垂直网站数据的医药知识图谱构建 2) 基于医药知识图谱的自动问答 +# 项目最终效果 +话不多少,直接上图。以下两图是实际问答运行过程中的截图: +![image](https://github.com/liuhuanyong/QABasedOnMedicalKnowledgeGraph/blob/master/img/chat1.png) + +![image](https://github.com/liuhuanyong/QABasedOnMedicalKnowledgeGraph/blob/master/img/chat2.png) + +# 项目运行: +1、配置要求:要求配置neo4j数据库及相应的python依赖包。neo4j数据库用户名密码记住,并修改相应文件。 +2、知识图谱数据导入:python build_medicalgraph.py,导入的数据较多,估计需要几个小时。 +3、启动问答:python chat_graph.py + # 一、医疗知识图谱构建 # 1.1 业务驱动的知识图谱构建框架 ![image](https://github.com/liuhuanyong/QABasedOnMedicalKnowledgeGraph/blob/master/img/kg_route.png) @@ -72,7 +83,6 @@ build_medicalgraph.py:知识图谱入库脚本    ![image](https://github.com/liuhuanyong/QABasedOnMedicalKnowledgeGraph/blob/master/img/qa_route.png) - # 2.2 脚本结构 question_classifier.py:问句类型分类脚本 question_parser.py:问句解析脚本 diff --git a/__pycache__/answer_search.cpython-36.pyc b/__pycache__/answer_search.cpython-36.pyc index 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zpG>CeVp3J*a=Je?+lrcEKb~N^+MiPM%*%XX!}faHq17`>v(CbmXm7N?pu%OyIbCw( zeV<+4QEVAMNLwN;?-w8w+42*`mLth*sSX{N-u}|MR`WNak@;NVK9My)jjc&A!IBy> zf?@etYzRM^Y*@ZObXXkMVzwWR$2YO7AEBGvRBU+oLE3^xY(K{Fy-^jrV)6=TZ#?G9;6NTn@uCI;qBOl1VfN$HjTiFcVa8} zRI-uy;ZVmAZs9tXI49^X7$}V}K;4cFNiZD4woe; ze=VpnkBeVnbNv3t6)WXTn6)f%T4GsY&axUVZPi6NZ&}+dyWS-k%c5@8vgCm$FGFcA zY*6fy2Mgl3l8bYk43Z~)^1uNl$>y^cWv%#>IK;H96`Y+4IX;Ih%xqu}Q)hfwb76Kd R(rHPyDGnZsuW4tp # Date: 18-10-5 -from py2neo import Graph,Node +from py2neo import Graph class AnswerSearcher: def __init__(self): @@ -13,17 +13,123 @@ class AnswerSearcher: http_port=7474, user="lhy", password="lhy123") + self.num_limit = 20 '''执行cypher查询,并返回相应结果''' def search_main(self, sqls): - for sql in sqls: - ress = self.g.run(sql).data() - for res in ress: - print(res) - return + final_answers = [] + for sql_ in sqls: + question_type = sql_['question_type'] + queries = sql_['sql'] + answers = [] + for query in queries: + ress = self.g.run(query).data() + answers += ress + final_answer = self.answer_prettify(question_type, answers) + if final_answer: + final_answers.append(final_answer) + return final_answers + '''根据对应的qustion_type,调用相应的回复模板''' + def answer_prettify(self, question_type, answers): + final_answer = [] + if not answers: + return '' + if question_type == 'disease_symptom': + desc = [i['n.name'] for i in answers] + subject = answers[0]['m.name'] + final_answer = '{0}的症状包括:{1}'.format(subject, ';'.join(list(set(desc))[:self.num_limit])) + elif question_type == 'symptom_disease': + desc = [i['m.name'] for i in answers] + subject = answers[0]['n.name'] + final_answer = '症状{0}可能染上的疾病有:{1}'.format(subject, ';'.join(list(set(desc))[:self.num_limit])) + + elif question_type == 'disease_cause': + desc = [i['m.cause'] for i in answers] + subject = answers[0]['m.name'] + final_answer = '{0}可能的成因有:{1}'.format(subject, ';'.join(list(set(desc))[:self.num_limit])) + + elif question_type == 'disease_prevent': + desc = [i['m.prevent'] for i in answers] + subject = answers[0]['m.name'] + final_answer = '{0}的预防措施包括:{1}'.format(subject, ';'.join(list(set(desc))[:self.num_limit])) + + elif question_type == 'disease_lasttime': + desc = [i['m.cure_lasttime'] for i in answers] + subject = answers[0]['m.name'] + final_answer = '{0}治疗可能持续的周期为:{1}'.format(subject, ';'.join(list(set(desc))[:self.num_limit])) + + elif question_type == 'disease_cureway': + desc = [i['m.cure_way'] for i in answers] + subject = answers[0]['m.name'] + final_answer = '{0}可以尝试如下治疗:{1}'.format(subject, ';'.join(list(set(desc))[:self.num_limit])) + + elif question_type == 'disease_cureprob': + desc = [i['m.cured_prob'] for i in answers] + subject = answers[0]['m.name'] + final_answer = '{0}治愈的概率为(仅供参考):{1}'.format(subject, ';'.join(list(set(desc))[:self.num_limit])) + + elif question_type == 'disease_easyget': + desc = [i['m.easy_get'] for i in answers] + subject = answers[0]['m.name'] + final_answer = '{0}的易感人群包括:{1}'.format(subject, ';'.join(list(set(desc))[:self.num_limit])) + + elif question_type == 'disease_desc': + desc = [i['m.desc'] for i in answers] + subject = answers[0]['m.name'] + final_answer = '{0},熟悉一下:{1}'.format(subject, ';'.join(list(set(desc))[:self.num_limit])) + + elif question_type == 'disease_acompany': + desc1 = [i['n.name'] for i in answers] + desc2 = [i['m.name'] for i in answers] + subject = answers[0]['m.name'] + desc = [i for i in desc1 + desc2 if i != subject] + final_answer = '{0}的症状包括:{1}'.format(subject, ';'.join(list(set(desc))[:self.num_limit])) + + elif question_type == 'disease_not_food': + desc = [i['n.name'] for i in answers] + subject = answers[0]['m.name'] + final_answer = '{0}忌食的食物包括有:{1}'.format(subject, ';'.join(list(set(desc))[:self.num_limit])) + + elif question_type == 'disease_do_food': + do_desc = [i['n.name'] for i in answers if i['r.name'] == '宜吃'] + recommand_desc = [i['n.name'] for i in answers if i['r.name'] == '推荐食谱'] + subject = answers[0]['m.name'] + final_answer = '{0}宜食的食物包括有:{1}\n推荐食谱包括有:{2}'.format(subject, ';'.join(list(set(do_desc))[:self.num_limit]), ';'.join(list(set(recommand_desc))[:self.num_limit])) + + elif question_type == 'food_not_disease': + desc = [i['m.name'] for i in answers] + subject = answers[0]['n.name'] + final_answer = '患有{0}的人最好不要吃{1}'.format(';'.join(list(set(desc))[:self.num_limit]), subject) + + elif question_type == 'food_do_disease': + desc = [i['m.name'] for i in answers] + subject = answers[0]['n.name'] + final_answer = '患有{0}的人建议多试试{1}'.format(';'.join(list(set(desc))[:self.num_limit]), subject) + + elif question_type == 'disease_drug': + desc = [i['n.name'] for i in answers] + subject = answers[0]['m.name'] + final_answer = '{0}通常的使用的药品包括:{1}'.format(subject, ';'.join(list(set(desc))[:self.num_limit])) + + elif question_type == 'drug_disease': + desc = [i['m.name'] for i in answers] + subject = answers[0]['n.name'] + final_answer = '{0}主治的疾病有{1},可以试试'.format(subject, ';'.join(list(set(desc))[:self.num_limit])) + + elif question_type == 'disease_check': + desc = [i['n.name'] for i in answers] + subject = answers[0]['m.name'] + final_answer = '{0}通常可以通过以下方式检查出来:{1}'.format(subject, ';'.join(list(set(desc))[:self.num_limit])) + + elif question_type == 'check_disease': + desc = [i['m.name'] for i in answers] + subject = answers[0]['n.name'] + final_answer = '通常可以通过{0}检查出来的疾病有{1}'.format(subject, ';'.join(list(set(desc))[:self.num_limit])) + + return final_answer if __name__ == '__main__': - searcher = AnswerSearch() \ No newline at end of file + searcher = AnswerSearcher() \ No newline at end of file diff --git a/chatbot_graph.py b/chatbot_graph.py index 0d720da..f6e1563 100644 --- a/chatbot_graph.py +++ b/chatbot_graph.py @@ -4,13 +4,11 @@ # Author: lhy # Date: 18-10-4 -import os - from question_classifier import * from question_parser import * from answer_search import * - +'''问答类''' class ChatBotGraph: def __init__(self): self.classifier = QuestionClassifier() @@ -18,18 +16,21 @@ class ChatBotGraph: self.searcher = AnswerSearcher() def chat_main(self, sent): - answer = '对不起,小生愚钝,祝您身体健康!每天开开心心的....' + answer = '您好,我是小勇医药智能助理,希望可以帮到您。如果没答上来,可联系https://liuhuanyong.github.io/。祝您身体棒棒!' res_classify = self.classifier.classify(sent) if not res_classify: - return + return answer res_sql = self.parser.parser_main(res_classify) - print(res_sql) - self.searcher.search_main(res_sql) - + final_answers = self.searcher.search_main(res_sql) + if not final_answers: + return answer + else: + return '\n'.join(final_answers) if __name__ == '__main__': handler = ChatBotGraph() while 1: - question = input('enter an question to search:') - handler.chat_main(question) + question = input('user:') + answer = handler.chat_main(question) + print('RoBot:', answer) diff --git a/dict/deny.txt b/dict/deny.txt index 572f886..e72b09c 100644 --- a/dict/deny.txt +++ b/dict/deny.txt @@ -32,3 +32,7 @@ 不可 别 管住 +注意 +小心 +少 + diff --git a/img/chat1.png 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z47soYBVqN+oe4V7?(mFwoFn35!b+cT?Qyt34K$!Q<0r_(#k1xLXZEetnh zdEt(GFBJg@8i2-A>#G%acOwla^K8L{L<2Bnx3+vM+5Ggjq@smIU1U2%l0S^vwugW0JilX22$-W!Gp7)pm2`fY8rr4ZS z%I?Uo*Sp9zLe~TTP!uYz{c&~&I0bs~2>)y2g7020kf+5-!h%<{k!B{=s^Y?%*4{Yi z(eIP(U%*pu?5nZ!^-w|WZeI=cmCIBWFlDN|8w?# jeXR+i|IhcyuYgL$m9Wa^mCtZF4nPs4DpxII`t^SSE&dTW literal 0 HcmV?d00001 diff --git a/question_classifier.py b/question_classifier.py index 084a50a..2ee72b8 100644 --- a/question_classifier.py +++ b/question_classifier.py @@ -35,7 +35,7 @@ class QuestionClassifier: self.wdtype_dict = self.build_wdtype_dict() # 问句疑问词 self.symptom_qwds = ['症状', '表征', '现象', '症候', '表现'] - self.cause_qwds = ['原因', '为什么', '怎么会', '怎样才', '咋样才', '怎样会', '如何会', '为啥', '为何', '如何', '怎么才会', '会导致', '会造成'] + self.cause_qwds = ['原因','成因', '为什么', '怎么会', '怎样才', '咋样才', '怎样会', '如何会', '为啥', '为何', '如何才会', '怎么才会', '会导致', '会造成'] self.acompany_qwds = ['并发症', '并发', '一起发生', '一并发生', '一起出现', '一并出现', '一同发生', '一同出现', '伴随发生', '伴随', '共现'] self.food_qwds = ['饮食', '饮用', '吃', '食', '伙食', '膳食', '喝', '菜' ,'忌口', '补品', '保健品', '食谱', '菜谱', '食用', '食物','补品'] self.drug_qwds = ['药', '药品', '用药', '胶囊', '口服液', '炎片'] @@ -48,7 +48,7 @@ class QuestionClassifier: self.cureway_qwds = ['怎么治疗', '如何医治', '怎么医治', '怎么治', '怎么医', '如何治', '医治方式', '疗法', '咋治', '怎么办', '咋办', '咋治'] self.cureprob_qwds = ['多大概率能治好', '多大几率能治好', '治好希望大么', '几率', '几成', '比例', '可能性', '能治', '可治', '可以治', '可以医'] self.easyget_qwds = ['易感人群', '容易感染', '易发人群', '什么人', '哪些人', '感染', '染上', '得上'] - self.check_qwds = ['检查', '检查项目'] + self.check_qwds = ['检查', '检查项目', '查出', '检查', '测出', '试出'] self.belong_qwds = ['属于什么科', '属于', '什么科', '科室'] self.cure_qwds = ['治疗什么', '治啥', '治疗啥', '医治啥', '治愈啥', '主治啥', '主治什么', '有什么用', '有何用', '用处', '用途', '有什么好处', '有什么益处', '有何益处', '用来', '用来做啥', '用来作甚', '需要', '要'] diff --git a/question_parser.py b/question_parser.py index b2ca1fa..39f6949 100644 --- a/question_parser.py +++ b/question_parser.py @@ -23,11 +23,10 @@ class QuestionPaser: args = res_classify['args'] entity_dict = self.build_entitydict(args) question_types = res_classify['question_types'] - sqls = [] - for question_type in question_types: - # print(question_type) + sql_ = {} + sql_['question_type'] = question_type sql = [] if question_type == 'disease_symptom': sql = self.sql_transfer(question_type, entity_dict.get('disease')) @@ -63,7 +62,7 @@ class QuestionPaser: sql = self.sql_transfer(question_type, entity_dict.get('disease')) elif question_type == 'check_disease': - sql = self.sql_transfer(question_type, entity_dict.get('disease')) + sql = self.sql_transfer(question_type, entity_dict.get('check')) elif question_type == 'disease_prevent': sql = self.sql_transfer(question_type, entity_dict.get('disease')) @@ -84,11 +83,12 @@ class QuestionPaser: sql = self.sql_transfer(question_type, entity_dict.get('disease')) if sql: - sqls += sql + sql_['sql'] = sql + + sqls.append(sql_) return sqls - '''针对不同的问题,分开进行处理''' def sql_transfer(self, question_type, entities): if not entities: @@ -112,6 +112,10 @@ class QuestionPaser: elif question_type == 'disease_cureprob': sql = ["MATCH (m:Disease) where m.name = '{0}' return m.name, m.cured_prob".format(i) for i in entities] + # 查询疾病的治疗方式 + elif question_type == 'disease_cureway': + sql = ["MATCH (m:Disease) where m.name = '{0}' return m.name, m.cure_way".format(i) for i in entities] + # 查询疾病的易发人群 elif question_type == 'disease_easyget': sql = ["MATCH (m:Disease) where m.name = '{0}' return m.name, m.easy_get".format(i) for i in entities]

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