Research And Design About Personalized Network Teaching Resource System

With the development of Internet, it has become an important way to obtaininformation. Users have the exponential growth of resources. But it has becomeincreasingly hard to find the information they want. Based on this, the developmentand utilization of personalized recommendation technology is a good solution tosolve information overload.Personalized recommendation is a kind of new intelligent information service.According to analyzing their requirements by user’s register and history of behavior,personalized recommendation can accurately provide the information users areinterested in. To a certain extent, personalized recommendation solves theinformation lost and information overload which brought about various problems.With the development of personalized recommendation technology research,popularization and application of the personalized recommendation system isbecoming the research hotspots.As an integral part of information technology, teaching resources play animportant role in education. At present, network teaching resource systems typicallyprovide the same resources to user. But users’ have different interests and hobbies.That is individual differences. The existing network teaching resources system cannot meet user’s personalized needs. Therefore, in order to achieve the goal ofpersonalized service to meet user, personalized recommendation technology isapplied to the system of online teaching resources.Through analyzing and comparing a lot of literature research, combining thecontent-based and collaborative filtering of personalized recommendation algorithmcan help users identify potential hobbies and make recommendations. It can helpusers quickly find that they need in a large number of information resources and meetusers’ demand for personalized service. As a result, this article uses combination ofthe content-based and collaborative filtering recommendation to recommendpersonalized teaching resources.First, the paper describes the problems of the current network of teachingresources and the research status of the individualized teaching services. Then thekey techniques of personal recommendation technology and user modeling areintroduced. Second, personal recommendation algorithm is the core of personalizedrecommendation system. Thereby, through analysis and comparison of existingpersonalized recommendation technology, content-based and collaborative filteringpersonalized recommendation algorithm is used, which achieves the function of personalized recommendation. For this reason, according to the characteristics ofusers as well as teaching resources, paper introduces the process of building the userinterest model and teaching resources model. The paper designs and implements theprototype of personalized online teaching resources. Based on this, we prove theeffectiveness of the personalized recommendation algorithm through experiments. Inthe end, the essay does simple summary and outlook on the content.