Research on Reverse Tailing Segmentation Optimization Algorithm in Intelligent Question Answering System of Physics Teaching

Abstract

In this stage, the massive increase of information data makes the information overload problem become more and more serious. How to effectively solve the problem has become a hot research topic for many experts and scholars. In the physics education, the application of the intelligent question answering system is becoming more extensive. As the traditional question answering system generally adopts the online value-checking method, there is a great deficiencies in the timeliness, and the provided answers are also not accurate enough. At this stage, most question-answering systems search the metadata through keywords, but for students, they tend to ask questions through natural language. In order to improve the information service quality in physics teaching, it is necessary to improve and optimize the algorithms of existing intelligent question answering system, to design an intelligent question answering system with natural language. In this view, this paper makes an in-depth study of the optimization of the inverse tailing segmentation algorithm in the physics teaching intelligent question answering system.