医疗知识图谱问答——文本分类解析

前言

        Neo4j的数据库构建完成后,现在就是要实现医疗知识的解答功能了。因为是初版,这里的问题解答不会涉及深度学习,目前只是一个条件查询的过程。而这个过程包括对问题的关键词拆解分类,然后提取词语和类型去图数据库查询,最后就是根据查询结果和问题类型组装语言完成回答,那么以下就是完成这个过程的全部代码流程了。

环境

        这里所需的环境除了前面提到的外,还需要ahocorasick库,用于从问题中提取关键词。另一个是colorama,用于给输出面板文字美化的库。

编码

1. 问答面板

from colorama import init,Fore,Style,Back
from classifier import Classifier
from parse import Parse
from answer import Answer

class ChatRobot:
    def __init__(self):
        init(autoreset=True)
        print("====================================")
        print(Back.BLUE+"欢迎进入智慧医疗问答面板!")
        print("====================================")

    def main(self, question):
        print("")

        default_answer = "您好,小北知识有限,暂时回答不上来,正在努力迭代中!"
        final_classify = Classifier().classify(question)
        parse_sql = Parse().main(final_classify)
        final_answer = Answer().main(parse_sql)

        if not final_answer:
            return default_answer

        return "\n\n".join(final_answer)

if __name__ == "__main__":
    robot = ChatRobot()
    while 1:
        print(" ")
        question = input("您问:")

        if "关闭" in question:
            print("")
            print("小北说:", "好的,已经关闭了哦,欢迎您下次提问~")
            break;

        answer = robot.main(question)

        print(Fore.LIGHTRED_EX+"小北答:", Fore.GREEN + answer)

2. 问题归类

import ahocorasick

class Classifier:
    def __init__(self):
        # print("开始初始化:", time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()))
        self.checks_wds = [i.strip() for i in open("dict/checks.txt", encoding="utf-8", mode="r") if i.strip()]
        self.departments_wds = [i.strip() for i in open("dict/departments.txt", encoding="utf-8", mode="r") if i.strip()]
        self.diseases_wds = [i.strip() for i in open("dict/diseases.txt", encoding="utf-8", mode="r") if i.strip()]
        self.drugs_wds = [i.strip() for i in open("dict/drugs.txt", encoding="utf-8", mode="r") if i.strip()]
        self.foods_wds = [i.strip() for i in open("dict/foods.txt", encoding="utf-8", mode="r") if i.strip()]
        self.producers_wds = [i.strip() for i in open("dict/producers.txt", encoding="utf-8", mode="r") if i.strip()]
        self.symptoms_wds = [i.strip() for i in open("dict/symptoms.txt", encoding="utf-8", mode="r") if i.strip()]
        self.features_wds = set(self.checks_wds+self.departments_wds+self.diseases_wds+self.drugs_wds+self.foods_wds+self.producers_wds+self.symptoms_wds)
        self.deny_words = [name.strip() for name in open("dict/deny.txt", encoding="utf-8", mode="r") if name.strip()]

        # actree 从输入文本中提取出指定分词表中的词
        self.actree = self.build_actree(list(self.features_wds))

        # 给每个词创建类型词典(相当慢的操作)
        self.wds_dict = self.build_words_dict()
        # print("给每个词创建类型词典结束:", time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()))

        # 问句疑问词
        self.symptom_qwds = ['症状', '表征', '现象', '症候', '表现']
        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']
        self.prevent_qwds = ['预防', '防范', '抵制', '抵御', '防止', '躲避', '逃避', '避开', '免得', '逃开', '避开', '避掉', '躲开', '躲掉', '绕开',
                             '怎样才能不', '怎么才能不', '咋样才能不', '咋才能不', '如何才能不',
                             '怎样才不', '怎么才不', '咋样才不', '咋才不', '如何才不',
                             '怎样才可以不', '怎么才可以不', '咋样才可以不', '咋才可以不', '如何可以不',
                             '怎样才可不', '怎么才可不', '咋样才可不', '咋才可不', '如何可不']
        self.lasttime_qwds = ['周期', '多久', '多长时间', '多少时间', '几天', '几年', '多少天', '多少小时', '几个小时', '多少年']
        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', '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']

    '''构造actree,加速过滤'''
    def build_actree(self, wordlist):
        actree = ahocorasick.Automaton()
        for index, word in enumerate(wordlist):
            actree.add_word(word, (index, word))
        actree.make_automaton()
        return actree

    # 构建特征词属性
    def build_words_dict(self):
        words_dict = {}
        check_words = set(self.checks_wds)
        department_words = set(self.departments_wds)
        disease_words = set(self.diseases_wds)
        drug_words = set(self.drugs_wds)
        food_words = set(self.foods_wds)
        producer_words = set(self.producers_wds)
        symptom_words = set(self.symptoms_wds)

        for word in self.features_wds:
            words_dict[word] = []
            if word in check_words:
                words_dict[word].append("check")
            if word in department_words:
                words_dict[word].append("department")
            if word in disease_words:
                words_dict[word].append("disease")
            if word in drug_words:
                words_dict[word].append("drug")
            if word in food_words:
                words_dict[word].append("food")
            if word in producer_words:
                words_dict[word].append("producer")
            if word in symptom_words:
                words_dict[word].append("symptom")

        return words_dict

    # 根据输入返回问题类型
    def classify(self, sent):
        # 最终输入给解析器的字典
        data = {}
        region_words = []
        lists = self.actree.iter(sent)
        for ii in lists:
            cur_word = ii[1][1]
            region_words.append(cur_word)

        # {'职业黑变病': ['diseases'], '倒睫': ['diseases', 'symptom']}
        final_dict = {i_name: self.wds_dict.get(i_name) for i_name in region_words}

        data['args'] = final_dict
        question_type = "other"
        questions_type = []

        # ['diseases', 'diseases', 'symptom']
        type = []
        for i_type in final_dict.values():
            type += i_type

        # 判断type中是否有指定类型, 提出的问题是否包含指定的修饰词,给问题定类型
        # 1. 如提问词是否出现状态词语,那就是问某种疾病会出现什么症状
        if self.check_word_exist(self.symptom_qwds, sent) and ('disease' in type):
            question_type = "disease_symptom"
            questions_type.append(question_type)

        # 根据症状问疾病
        if self.check_word_exist(self.symptom_qwds, sent) and ('symptom' in type):
            question_type = "symptom_disease"
            questions_type.append(question_type)

        # 原因
        if self.check_word_exist(self.cause_qwds, sent) and ('disease' in type):
            question_type = 'disease_cause'
            questions_type.append(question_type)

        # 并发症
        if self.check_word_exist(self.acompany_qwds, sent) and ('disease' in type):
            question_type = 'disease_acompany'
            questions_type.append(question_type)

        # 推荐食品
        if self.check_word_exist(self.food_qwds, sent) and 'disease' in type:
            deny_status = self.check_word_exist(self.deny_words, sent)
            if deny_status:
                question_type = 'disease_not_food'
            else:
                question_type = 'disease_do_food'
            questions_type.append(question_type)

        # 已知食物找疾病
        if self.check_word_exist(self.food_qwds + self.cure_qwds, sent) and 'food' in type:
            deny_status = self.check_word_exist(self.deny_words, sent)
            if deny_status:
                question_type = 'food_not_disease'
            else:
                question_type = 'food_do_disease'
            questions_type.append(question_type)

        # 推荐药品
        if self.check_word_exist(self.drug_qwds, sent) and 'disease' in type:
            question_type = 'disease_drug'
            questions_type.append(question_type)

        # 药品治啥病
        if self.check_word_exist(self.cure_qwds, sent) and 'drug' in type:
            question_type = 'drug_disease'
            questions_type.append(question_type)

        # 疾病接受检查项目
        if self.check_word_exist(self.check_qwds, sent) and 'disease' in type:
            question_type = 'disease_check'
            questions_type.append(question_type)

        # 已知检查项目查相应疾病
        if self.check_word_exist(self.check_qwds + self.cure_qwds, sent) and 'check' in type:
            question_type = 'check_disease'
            questions_type.append(question_type)

        #  症状防御
        if self.check_word_exist(self.prevent_qwds, sent) and 'disease' in type:
            question_type = 'disease_prevent'
            questions_type.append(question_type)

        # 疾病医疗周期
        if self.check_word_exist(self.lasttime_qwds, sent) and 'disease' in type:
            question_type = 'disease_lasttime'
            questions_type.append(question_type)

        # 疾病治疗方式
        if self.check_word_exist(self.cureway_qwds, sent) and 'disease' in type:
            question_type = 'disease_cureway'
            questions_type.append(question_type)

        # 疾病治愈可能性
        if self.check_word_exist(self.cureprob_qwds, sent) and 'disease' in type:
            question_type = 'disease_cureprob'
            questions_type.append(question_type)

        # 疾病易感染人群
        if self.check_word_exist(self.easyget_qwds, sent) and 'disease' in type:
            question_type = 'disease_easyget'
            questions_type.append(question_type)

        # 若没有查到相关的外部查询信息,那么则将该疾病的描述信息返回
        if questions_type == [] and 'disease' in type:
            questions_type = ['disease_desc']

        # 若没有查到相关的外部查询信息,那么则将该疾病的描述信息返回
        if questions_type == [] and 'symptom' in type:
            questions_type = ['symptom_disease']

        # 将多个分类结果进行合并处理,组装成一个字典
        data['question_types'] = questions_type

        return data

    def check_word_exist(self, word_list, words):
        for item in word_list:
            if item in words:
                return True

        return False

3. 类型解析(查询组装)


class Parse:

    def main(self, classify):
        entity = classify['args']
        questions_type = classify['question_types']
        entity_dict = self.entity_transform(entity)

        sqls = []
        for question in questions_type:
            sql_dict = {}
            sql_dict["qustion_type"] = question
            sql_dict["sql"] = []
            sql = []
            if question == 'disease_symptom':
                sql = self.sql_transfer(question, entity_dict.get('disease'))

            elif question == 'symptom_disease':
                sql = self.sql_transfer(question, entity_dict.get('symptom'))

            elif question == 'disease_cause':
                sql = self.sql_transfer(question, entity_dict.get('disease'))

            elif question == 'disease_acompany':
                sql = self.sql_transfer(question, entity_dict.get('disease'))

            elif question == 'disease_not_food':
                sql = self.sql_transfer(question, entity_dict.get('disease'))

            elif question == 'disease_do_food':
                sql = self.sql_transfer(question, entity_dict.get('disease'))

            elif question == 'food_not_disease':
                sql = self.sql_transfer(question, entity_dict.get('food'))

            elif question == 'food_do_disease':
                sql = self.sql_transfer(question, entity_dict.get('food'))

            elif question == 'disease_drug':
                sql = self.sql_transfer(question, entity_dict.get('disease'))

            elif question == 'drug_disease':
                sql = self.sql_transfer(question, entity_dict.get('drug'))

            elif question == 'disease_check':
                sql = self.sql_transfer(question, entity_dict.get('disease'))

            elif question == 'check_disease':
                sql = self.sql_transfer(question, entity_dict.get('check'))

            elif question == 'disease_prevent':
                sql = self.sql_transfer(question, entity_dict.get('disease'))

            elif question == 'disease_lasttime':
                sql = self.sql_transfer(question, entity_dict.get('disease'))

            elif question == 'disease_cureway':
                sql = self.sql_transfer(question, entity_dict.get('disease'))

            elif question == 'disease_cureprob':
                sql = self.sql_transfer(question, entity_dict.get('disease'))

            elif question == 'disease_easyget':
                sql = self.sql_transfer(question, entity_dict.get('disease'))

            elif question == 'disease_desc':
                sql = self.sql_transfer(question, entity_dict.get('disease'))

            if sql:
                sql_dict['sql'] = sql

                sqls.append(sql_dict)

        return sqls

    def sql_transfer(self, question_type, entities):
        # 查询语句
        sql = []
        # 查询疾病的原因
        if question_type == 'disease_cause':
            sql = ["MATCH (m:Diseases) where m.name = '{0}' return m.name, m.cause".format(i) for i in entities]

        # 查询疾病的防御措施
        elif question_type == 'disease_prevent':
            sql = ["MATCH (m:Diseases) where m.name = '{0}' return m.name, m.prevent".format(i) for i in entities]

        # 查询疾病的持续时间
        elif question_type == 'disease_lasttime':
            sql = ["MATCH (m:Diseases) where m.name = '{0}' return m.name, m.cure_lasttime".format(i) for i in entities]

        # 查询疾病的治愈概率
        elif question_type == 'disease_cureprob':
            sql = ["MATCH (m:Diseases) 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:Diseases) 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:Diseases) where m.name = '{0}' return m.name, m.easy_get".format(i) for i in entities]

        # 查询疾病的相关介绍
        elif question_type == 'disease_desc':
            sql = ["MATCH (m:Diseases) where m.name = '{0}' return m.name, m.desc".format(i) for i in entities]

        # 查询疾病有哪些症状
        elif question_type == 'disease_symptom':
            sql = [
                "MATCH (m:Diseases)-[r:has_symptoms]->(n:Symptoms) where m.name = '{0}' return m.name, r.name, n.name".format(
                    i) for i in entities]

        # 查询症状会导致哪些疾病
        elif question_type == 'symptom_disease':
            sql = [
                "MATCH (m:Diseases)-[r:has_symptoms]->(n:Symptoms) where n.name = '{0}' return m.name, r.name, n.name".format(
                    i) for i in entities]

        # 查询疾病的并发症
        elif question_type == 'disease_acompany':
            sql1 = [
                "MATCH (m:Diseases)-[r:acompany_with]->(n:Symptoms) where m.name = '{0}' return m.name, r.name, n.name".format(
                    i) for i in entities]
            sql2 = [
                "MATCH (m:Diseases)-[r:acompany_with]->(n:Symptoms) where n.name = '{0}' return m.name, r.name, n.name".format(
                    i) for i in entities]
            sql = sql1 + sql2
        # 查询疾病的忌口
        elif question_type == 'disease_not_food':
            sql = ["MATCH (m:Diseases)-[r:not_eat]->(n:Foods) where m.name = '{0}' return m.name, r.name, n.name".format(i)
                   for i in entities]

        # 查询疾病建议吃的东西
        elif question_type == 'disease_do_food':
            sql1 = [
                "MATCH (m:Diseases)-[r:do_eat]->(n:Foods) where m.name = '{0}' return m.name, r.name, n.name".format(i)
                for i in entities]
            sql2 = [
                "MATCH (m:Diseases)-[r:recomment_eat]->(n:Foods) where m.name = '{0}' return m.name, r.name, n.name".format(
                    i) for i in entities]
            sql = sql1 + sql2

        # 已知忌口查疾病
        elif question_type == 'food_not_disease':
            sql = ["MATCH (m:Diseases)-[r:not_eat]->(n:Foods) where n.name = '{0}' return m.name, r.name, n.name".format(i)
                   for i in entities]

        # 已知推荐查疾病
        elif question_type == 'food_do_disease':
            sql1 = [
                "MATCH (m:Diseases)-[r:do_eat]->(n:Foods) where n.name = '{0}' return m.name, r.name, n.name".format(i)
                for i in entities]
            sql2 = [
                "MATCH (m:Diseases)-[r:recomment_eat]->(n:Foods) where n.name = '{0}' return m.name, r.name, n.name".format(
                    i) for i in entities]
            sql = sql1 + sql2

        # 查询疾病常用药品-药品别名记得扩充
        elif question_type == 'disease_drug':
            sql1 = [
                "MATCH (m:Diseases)-[r:common_drug]->(n:Drugs) where m.name = '{0}' return m.name, r.name, n.name".format(
                    i) for i in entities]
            sql2 = [
                "MATCH (m:Diseases)-[r:recommand_drug]->(n:Drugs) where m.name = '{0}' return m.name, r.name, n.name".format(
                    i) for i in entities]
            sql = sql1 + sql2

        # 已知药品查询能够治疗的疾病
        elif question_type == 'drug_disease':
            sql1 = [
                "MATCH (m:Diseases)-[r:common_drug]->(n:Drugs) where n.name = '{0}' return m.name, r.name, n.name".format(
                    i) for i in entities]
            sql2 = [
                "MATCH (m:Diseases)-[r:recommand_drug]->(n:Drugs) where n.name = '{0}' return m.name, r.name, n.name".format(
                    i) for i in entities]
            sql = sql1 + sql2
        # 查询疾病应该进行的检查
        elif question_type == 'disease_check':
            sql = [
                "MATCH (m:Diseases)-[r:need_check]->(n:Checks) where m.name = '{0}' return m.name, r.name, n.name".format(
                    i) for i in entities]

        # 已知检查查询疾病
        elif question_type == 'check_disease':
            sql = [
                "MATCH (m:Diseases)-[r:need_check]->(n:Checks) where n.name = '{0}' return m.name, r.name, n.name".format(
                    i) for i in entities]

        return sql

    def entity_transform(self, entity):
        entity_dict = {}
        for args, types in entity.items():
            for type in types:
                if type in entity_dict:
                    entity_dict[type] = [args]
                else:
                    entity_dict[type] = []
                    entity_dict[type].append(args)
        return entity_dict

4. 数据查询(回答组装)

from py2neo import Graph, Node

class Answer:
    def __init__(self):
        self.neo4j = Graph('bolt://localhost:7687', auth=('neo4j', 'beiqiaosu123456'))
        self.num_limit = 20

    def main(self, question_parse):
        answers_final = []
        for item in question_parse:
            question_type = item['qustion_type']
            sqls = item['sql']
            answer = []
            for sql in sqls:
                data = self.neo4j.run(sql)
                answer+=data.data()

            final_answer = self.answer_prettify(question_type, answer)
            if final_answer:
                answers_final.append(final_answer)

        return answers_final

    '''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 = [';'.join(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'] == '可以吃']
            recommand_desc = [i['n.name'] for i in answers if i['r.name'] == '推荐吃']
            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

写在最后

        以上就是这个医疗知识问答机器人的全部代码了,从上面的问答里也能看出,回答得还是很生硬。因为这就只是一个程序化得思维导图,所以修改完善空间还是很大,这个就要后期用深度学习得方式对分类解析部分进行改动。

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