Learning Object Recommendation Based On QoS

E-Learning is leaning activities that based on Internet and digital contents.It is a new learning pattern that utilizes modern information technology,has new communication mechanism and learning environment with enrich resources. E-Learning changes the teachers'affect in traditional learning and the relationship between teachers and learners. The learning structure and education essence are changed by E-Learing.To support personalized learning process becomes more and more important in E-Learning. Personalized learning process is that to recommend different learning path and learning-object to individual according to their interesting, performance and kownledge level, help learners to achieve their learng goals. The distributed reasource environment on Internet can strongly support E-Learning in cooperation learning. This paper research on E-Learning framework and personalized learning content recommendation technology.This paper firstly analyzes the E-Learning model, the key technology, reviews and summarizes the typical research projects and experimental systems at home and abroad, and comes up with the processing idea and the framework of personalized learning content recommendation system. This paper next turns to the discussion of the AEHS, which is a key step in realizing personalized function in recommended system ,and then studies the four aspects: Domain Model, User Model, Adaptation Model, Adaptive Engine.It thirdly explores in E-Learning environment the application of learning resource standards and learning objects , which support personalized learning in some parts. And next the in-depth analysis on E-Learning personalized learning points out that the root cause lies in the lack of semantics in resources and the weak sharing mechanisms in system, then proposes a dynamic learning modeling,and realizing dynamic learner modeling in the AEHS,and improving individualized learning through enhancing personalized learning content recommendation capabilities of E-Learning.The research on personalized recommendation algorithm is the last part of this paper.To support rapid and dynamic composition of learning-object in learning process,learing object that meet learners'functional requirements must be able to be located and bounded dymamically from a large and constantly changing number of learning-object providers based ont their Quality of Service (QoS).In order to enable quality-driven learning-object, this paper proposed an open, fair, dynamic and secure algorithm to evaluate the QoS of a vast number of learing-object through implementation of and experimentation.