Intelligent Question Answering System Based on Domain Knowledge Graph

Abstract

This paper introduces an intelligent question answering system based on the domain knowledge graph of military battle cases. Through the collection and accumulation of military big data, we first build a domain knowledge graph for military battle cases, and then use natural language processing related technologies to understand natural language problems, mainly intention recognition and slot filling. On problem intent identification. In this paper, BERT+TextCNN model is proposed to realize the intention classification of questions. LAC is used to segment the natural language questions and extract the entities in the question sentence in slot filling. The answer is then retrieved from the knowledge graph. The test results show that the accuracy of question comprehension in the question set is more than 90%, and it can answer most of the questions in the field quickly and accurately.