A Classified Question and Answer System Based on SpringBoot Integrated Neo4j Graph Database

With the development of artificial intelligence, natural language processing is more and more widely used in daily life. Firstly, this paper explains the project background of the classification question answering system based on SpringBoot integrated with Neo4j graph database, and introduces the relevant parts of the technology. And then focus on intelligent question answering system to build the actual system on film industry. User input would firstly use HanLP word recognition to split out the statement, then match the template using the naive bayesian classifier to identify most appropriate template, finally to replace the phrase with a phrase or secondary database query. This automatic question and answer system provides user a more convenient way to know about the movie information user interested in. In this paper, HanLP and Naive Bayes are used to implement an intelligent classified question-answering system. Other functions in the system include automatic daily update of movie information, classic movie dialogue and related movie videos are integrated by using third-party API. The actual operation of the system is smooth and the user experience is good.