基于新聚类算法的推荐系统的研究与实现

针对目前远程教育中,学员数目日渐增多、水平参差不齐而教师资源短缺而无法因材施教等问题,文章构建了一个基于逐层降维聚类分析方法的资源推荐系统。该系统通过基于知识树的聚类分析将学员分为不同的社区,由教师为社区推荐学习资源以对学员进行相对个性化的学习指导。实验结果表明,该系统大大缩减了授课教师的工作量,并且有效地提高了学员的学习质量和学习效率;同时这种迅速动态聚类方法可以很好地将散布的学员组织在一起,满足了学员相互之间的交流、推荐需求。

Research and Implementation of a Resource Recommendation System Based on a New Clustering Analysis Algorithm

Aiming at the disadvantages such as increasing number of e-learners,diversity in learner profiles and great shortage of teachers in E-learning environment,a recommendation system based on technology of clustering analysis using dimensionality reduction method was proposed.It divides learners into different communities dynamically for relatively personalized recommendation on learning resources and guidance by clustering analysis.Experimental results show that the system takes off the heavy burden of the tea...