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college_kbqa

基于知识图谱的高校信息查询系统

哔哩哔哩账号

name:小倪要一直努力呀

关于模型的构建和代码讲解我都会在b站实时更新,b站代码讲解要比github上传的慢一点,大家见谅

整体流程

  1. 当第一次询问时会进行第一次意图识别判断你是 询问高校 闲聊

如果是闲聊,则回复对应的闲聊问答,如果是询问高校则判断是询问那一部分高校信息

  1. 当询问是关于高校信息时,进行第二次意图识别,判断是哪一类高校信息 询问地址 询问专业 询问。。。

会对第二次的询问做一个softmax,如果是 p>0.65, 则直接进行ner, 如果在0.4<p<0.65直接会返回询问确定问题,低于0.4,直接进入faq返回问答

  1. 在ner中,会识别实体,如果得到实体链接后,直接进入neo4j做槽位填充

当在基于第一个问题基础上询问第二个问题是,有类别无实体,则默认第一个问题实体,有实体无类别,则默认第一个类别,做意图继承和实体继承

  1. faq作文整个知识图谱的辅助部分,所有的不确定语句或者不属于规定类别范围的语句全部进入faq部分,返回相似问答,faq语句是基于simbert做的相似度回归,后期会与elasticsearch联合做一个相似度的打分。

垂直领域知识图谱,问题查询

  • 基于学校查历史
  • 查询排名
  • 查询学科排名
  • 查询就业去向
  • 招生办电话
  • 综合信息。。。等等十二个类别

多轮对话机制

  • 意图继承
  • 主体继承

faq问答

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