Research and Application of Knowledge Graph Technology for Intelligent Question Answering

With the development and application of artificial intelligence technology, knowledge graph gradually becomes one of the key technologies. To solve the data sparsity problem of knowledge graph and improve the efficiency of knowledge graph completion, a knowledge representation model (ISTransE) was proposed, which combined the importance information of entities and relationship strength characteristics. We combine the BERT model and knowledge graph to study the key technology of Q&A, complete the relevant design of an intelligent Q&A system. And realize the intelligent Q&A system of automobiles based on the BERT entity recognition module, question relationship extraction module, answer retrieval module and construct the domain knowledge graph module. And the system is tested by corresponding experiments for Q&A. The test results show that this system can accurately answer the user's car-related knowledge.