The Design And Implementation Of Instructional Videos Recommendation System Based On Tag

With the rapid development and maturity of Internet and multimedia technology, online education as a new convenient and efficient teaching method suddenly comes into the view of people; especially video teaching is one of the most important accesses to knowledge with rich information forms and fast delivery channels. It can not only help users’ self-learning process, but also help teachers to carry out their teaching activities efficiently. When meeting the massive video resources, learners may feel "lost". How to help them to find the demanded resources and satisfy their personalized needs has become a problem we need to deal with.On the basis of above, this article will integrate tagging with personalized recommendation technology, to analyze the interests of users through their tagging behaviors, thus the matched video resources can be recommended automatically. In this article, the user-tag correlation matrix and the collaborative filtering recommendation technology are applied to construct the recommendation model based on tagging. And by using the technologies like ASP.NET, JavaScript, B/S three layer architecture models, etc., the design and development of video teaching system have been completed. This system has the functions of recommending, searching and playing instructional Videos, managing user’s personal resource, tagging, scoring, and interactive communication etc. It aims at providing personalized video recommendation service to meet user’s demand for independent learning.The prototype of the video recommendation system is running well in the test. On the one hand, the system provides a platform for interaction between teachers and students, and meets the different needs of them; on the other hand, it has managed to offering personalized resource service to improve learners’ learning efficiency and learning effects.