Research Of Personalized Learning System In The Knowledge

With the development of internet technology and application, E-Learning hasbecome a new way of learning. It is not restricted by time and space whenever andwherever possible to provide learners with rich and open learning resources, whichis popular, has quickly become one of the most important forms of moderneducation and teaching system. But in the process of rapid development ofE-Learning, learners always face this problems as follows as a result of the rapidexpansion of the number of learning resources in the platform: Firstly, informationoverload. Even if you spend a lot of time and effort to access and retrieve learningresources, you may find that learning resource information what you got in line notalways conform to their own interests and needs; Secondly, platform constructionstill remains in the level of material-based, ignoring the leaner’s personalizedfeatures, can not meet the needs of users. Therefore, the goal of knowledge pushsystem is quickly and effectively to provide users with the appropriate resourceinformation.This article studies of the personalized knowledge push system has thefollowing contents: Firstly, introduced the background information and the currentdevelopment situation of the personalized recommendation system at home andabroad; Secondly, expounded the theory and technology of personalizedrecommendation, detailing common personalization recommendation technology;and at the basis of combining with the content filtering algorithm and collaborativefiltering recommendation algorithm, the author raised an optimized combination ofrecommendation algorithm, to some extent, which can alleviate the traditional ofrecommendation algorithm sparse data and cold start problems. Thirdly, theintroduction of the implicit rating mechanism, a system to track and record theleaner’s learning behavior, the extraction behavior of learning user preferenceweighted transformed into a user rating of resources, increase user ratings rate ofresources, which can effectively solve the collaborative algorithm “orating”problem; once again, according to the personalized knowledge push systemas you want to achieve the goals and function, proposed a personalized knowledgepush system framework to grasp the personalized push the system’s design from themacro. Finally, designed personalized knowledge push system.