作　　者： ; ; ; ;

机构地区： 浙江工业大学教育科学与技术学院

出　　处： 《远程教育杂志》 2011年第3期66-71,共6页

摘　　要： e-learning的调查发现,e-learning支持系统中学习资源推荐主要有Top-N和关键词检索两种方式,都无法向学习者个性化地推荐学习资源。受电子商务研究领域中相关研究成果启发,我们尝试将协同过滤推荐技术引入学习资源的个性化推荐研究中。通过综述学习资源个性化推荐中三种常用的推荐技术,介绍了协同过滤推荐技术的工作原理、实现方法及存在问题。在此基础上,提出了一个优化的基于协同过滤技术的学习资源个性化推荐系统的理论模型,重点讨论了模型的结构、隐式评分机制和算法的实现,并讨论了个性化学习资源推荐模型中的三个关键技术。以启发e-learning研究人员从不同的层面和角度探索协同过滤技术在e-learning中的应用,提高学习资源个性化推荐的精度和效率。 According to the survey of e-learning,we find that there are two ways to recommend resources in the support system of e-learning system,they are Top-N and Keywords retrieving,but both of them are not able to recommend resources personalized.Be inspired by the research achievement in e-commerce fields,we try to introduce the collaborative filtering technology into research of personalized recommendation of learning resources.This paper summarizes three common recommendation technology of the Learning resource personalized recommending.On this basis,we first put forward a optimized theoretical model of personalized recommendation system of learning resources based on collaborative filtering recommendation technology,then discuss the structure of the model,analyze the mechanism of implicit rating system,finally introduce the realization method of the collaborative filtering recommendation algorithm.We expect that this paper could inspire the researchers of e-learning to explore collaborative filtering technology from different aspects in the e-learning application,in order to improve the accuracy and efficiency of the personalized recommendation of learning resources.

关 键 词： 协同过滤技术 学习资源 个性化推荐

领　　域： [自动化与计算机技术] [自动化与计算机技术]