计算机与数字工程2025，Vol.53Issue(2)：358-363,383,7.DOI:10.3969/j.issn.1672-9722.2025.02.011
领域知识图谱构建及复杂问答方法研究
Research on Domain Knowledge Graph Construction and Complex Question Answering Approach
摘要
Abstract
The existing mature Chinese knowledge graph question answering methods can only answer some simple questions well,and it is difficult to deal with complex questions such as aggregation,comparison,multi hop and counting.Taking the field of party history as an example,this paper uses semi-automatic technology to construct the knowledge graph of party history.Then,a multi-task question answering model combining entity recognition,path prediction,question type recognition and answer entity type prediction is proposed to process complex questions.Finally,the validity of the model is proved by experimental analysis and question answering test.As a knowledge graph of party history and a complex Chinese question answering,this paper makes a pre-liminary beneficial exploration.关键词
知识图谱/自然语言处理/多任务问答模型/复杂问答方法Key words
knowledge graph/natural language processing/multi-task question answering model/complex question answer-ing approach分类
信息技术与安全科学引用本文复制引用
李华昱,王佳坤,闫阳,李家瑞..领域知识图谱构建及复杂问答方法研究[J].计算机与数字工程,2025,53(2):358-363,383,7.基金项目
山东省自然科学基金项目(编号:ZR2020MF140) （编号:ZR2020MF140）
中国石油大学(华东)研究生创新工程(编号:YCX2021128)资助. （华东）
