The Design And Implementation Of The Multimedia Teaching System Of Hegang Normal College Based On Collaborative Filtering Algorithm

With the popularization of information technology and Internet, Network has become an indispensable part of the students learning life. Online learning is one of the main ways of information society learning. Due to a wide range of learning resources, sometimes the information search is aimless, so it is difficult for us to find the learning goals. Along with the practice of application, the quantity of learning content of many platforms is increasing.We found that the ways of the current network learning that push resources are: Top- N recommence, the keyword query and the recommence of the latest resources. It’s common that the recommendation technology applied in shopping network, movie website, etc. The above delivery methods of all kinds of learning content,to some extent,can help learners retrieve and find the resources that they love. But we cannot push the personalized learning resources to the learners. Therefore, how to solve the personalized recommending about the learning resources of the network platform becomes a theme that the current researchers in the field of technology education face at present. Some scholars in the field of teaching also started to use the personalized recommendation algorithm in order to recommend their favorite teaching resources to learners. So it is very necessary to recommend a personalized learning resource according to the different interests of students.Collaborative filtering techniques have been applied in personalized recommendation system, with the number of users of the system of electronic commerce and commodity number increasing, the whole project on the space user ratings data is extremely sparse, there exist certain disadvantages to the traditional test method of similarity. On the basis ofintroducing project score predictions, considering the problems of data sparseness, the project similarity is calculated by the good methods of conditional probability, and collaborative filtering recommendation algorithm optimization is raised, so the calculation result are practical and accurate. Experiments prove that the algorithm can effectively avoid the disadvantages of traditional method, improving the recommended quality of the system.This paper designs and implements a multimedia teaching system based on collaborative filtering algorithm, making the boring text represented in vivid multimedia. This system includes the foreground system and the background system. Users of the system at the front desk for viewing the teaching resources, can download, message, and evaluation, etc.The background system is mainly used for the administrator to do the management work. This article recommends that the teaching resources are graded in the way of explicit rating score by the system users,and then based on the user’s collaborative filtering and the collaborative filtering of the project, teaching resources are recommended to the users. This system consists of four types of teaching resources, they are video, audio, courseware and notes respectively. Courseware are PPT format, notes are DOC format.Auxiliary teaching through the teaching system, to a certain extent, is helpful for the students and teachers to share better teaching resources and communicate, also students may learn independently, and the study effect is greatly improved. By introducing a collaborative filtering recommendation algorithm into the network platform, we make the algorithm go into a new application field, in order to inspire more researchers from different aspects and angles to explore collaborative filtering technology in the application of network, improving the efficiency of the personalized resources.