Design and Simulation of Intelligent Matching Algorithm for Online Primary School Mathematics Curriculum Based on Deep Learning

With the continuous development of new information technologies such as big data, cloud computing, and Internet of Things, people's access to knowledge and information has undergone profound changes. New concepts such as machine learning, wisdom education, and educational big data are changing the traditional educational ecology, teaching form, and learning methods, and at the same time, promoting the deep development of educational modernization to informationization. People's needs in the fields of artificial intelligence such as information retrieval, automatic question and answer, dialogue system, etc. begin to appear, and intelligent matching algorithms are needed to meet the high demand of users. Text matching algorithm is the core problem in natural language processing technology. In the traditional text matching field, the dimension disaster of text representation and data sparseness have affected the development of natural language processing field. It is necessary for the times and students’ development to carry out subject teaching under the guidance of deep learning, which is of great significance. Unit review class is an important class type of primary school mathematics, which is of great value to students’ development, but there are many problems in actual teaching. This paper presents a multi-view collaborative teaching network based on sparse interactive data. The matching network is mainly composed of two parts, a text-based matching model and a relationship-based matching model.