Course Question Answering System Based on Artificial Intelligence

Abstract

With the rapid update of artificial intelligence technology and network technology, modern distance education has developed rapidly and has gradually become an important part of the modern education field, which has attracted great attention from the education and computer circles. The course question answering system based on artificial intelligence is an indispensable part of the modern distance education teaching process and plays an important role in assisting teaching. The purpose of this article is to research the course answering system based on artificial intelligence. This paper introduces the concept of artificial intelligence Agent into the research of question answering system. Under the guidance of constructivist learning theory, using natural language processing technology and personalized recommendation technology to design and develop an artificial intelligence network intelligent answering system based on multi-agent. This paper studies the three key technologies to realize the artificial intelligence answering system, namely natural language processing technology, personalized recommendation technology and the structure and organization of the knowledge base. This paper proposes a multi-agent-based artificial intelligence network answering system model, implements the prototype system, and analyzes the system structure and workflow in detail. This article aims to improve the recall and accuracy of problem text clustering. Applying association rules to each type of problem after clustering can obtain a more accurate association table, and at the same time promote the accuracy of similarity to be improved. This loop operation can improve the answering speed and accuracy. Experimental research shows that when the number of transactions is 300, a takes 0.878, and B takes 0.037, the highest accuracy of answering questions can be obtained.