Research On Personalized Resource Recommendation In Distance Educational Resource Network

Nowadays the development in ubiquitous computing and networking has changingthe current teaching mode. The digitization and networking of educational resourcesbecomes an inevitable trend. It is difficult to retrieve and share resources. Learners arepuzzled by the problem of “information overload” and “information trek”. Therefore,personalized recommendation service for learners become to be researched and solvedin distance education system.This paper draws personalized recommendation technology into the field ofdistance education. Firstly, the paper analyzes the current status of educational resourcesconstruction and exsited problems. It is proposed that educational resources can bedescribed as learning object metadata under the framework of CELTS standard andLOM specification. Detailed description of methods and extension mechanism iscovered. Secondly, the specific ideas and solutions of personalized resourcerecommendation in educational network are discussed. It focuses on the current popularpersonalized recommendation algorithms. In the analysis of various algorithms based onthe advantages and disadvantages, we apply an algorithm combing User-basedrecommendation and Item-based collaborative filtering into personalizedrecommendation system. By Movielens experiments on the dataset, combinationalgorithm to some extent, can improve the problem of data sparsity and amelioraterecommendation quality. In the end, the entire framework of personalizedrecommendation system is designed and the implementation process ofrecommendation service is described in detail.