Research & Implementation Of Individualized Resource Recommendation System Based On Blending Technology

In the age with rapid development and high popularity in networks technology and information technology, E-Learning has becoming a significant path to cultivate talents, improve scientific research and develop education. However, support from rich education resources is a necessity in order to serve education effeciently and optimize education process and resources with networks and information technology, so constructing a perfect and sufficent web education resource system is the premise for us to develop E-Learning.Up to now, majority of education resource-lib system is only equiped with functions of resource uploading, searching and downloading which still stay in the phase of product-oriented instead of human-oriented thought. The glaring problem for education resource-lib system is lack of characteristics of individualization and intelligentization which leads to a conflict between mass storage of education resources and individual request of users, it becomes an epitome of "knowledge starvation in information blasting". This long-term exisited conflict not only lowers the utilization of education resources, but makes trouble in users' searching and utilization for education resources which directly hamper their effect in education.The research in this paper aimed at designing and implementing a feasible individualized resource recommendation solution to promote the individualization and intelligentization of education recource-lib system, and solve the problems in searching resources and low-efficient utilization of it.Work in this paper mainly includes:1) Aimed at the conflict between large amount of education resources and users' individual needs nowadays, this research developed and built a education resources knowledge-lib system which is used as a foundational platform in which implemented a individualized resource recommendation serive prototype model. This model brings the web based individualized information service into education resource system,puts emphasis on diversity between different users,tracks and logs users' individual information and behaviour through whcih the model recommends education resources to fit demands of different users.2) Made analysis and research on the disadvantages of exsiting recommendation algorithms and recommdation model, brought out a kind of blending recommendation technology. This recommendation technology applied the demographic data analysis technology which is used in clustering, it solved the problems of new user recommdation and low-density in user scores. Compared to the traditional recommdation algorithms, it obviously improved the accuracy and quality of recommdation.3) Designed and implemented a research experiment based on education resource knowledge system and indidualized resource recommendation prototype model, which includes contrast experiment between blending recommendation technology and traditional one, finally gained plenty of experimental data. Data analysis was worked on these experimental data and the results indicated that individualized resource recommendation system in this paper which based on blending recommendation techonolgy provided higher accuration and obviously improved the recommendation quality.Three papers related to this research have been published or accepted by key journals in China.