计算机应用研究2017，Vol.34Issue(12)：3725-3729,5.DOI:10.3969/j.issn.1001-3695.2017.12.047
基于隐式评分和相似度传递的学习资源推荐
Learning resource recommendation based on implicit scoring and similarity propagation
摘要
Abstract
Traditional collaborative filtering recommendation algorithm has the problem of sparse data,which makes the learning needs of users cannot be satisfied because of the sparsity of user learning behavior records.To address this issue,this paper proposed a learning resource recommendation algorithm based on implicit rating and similarity propagation.Firstly,it collected the user's learning behavior.Secondly,it improved the calculation method of similarity.On the basis of this,it introduced the similarity propagation strategy.Finally,it applied and implemented the collaborative filtering algorithm based on personalized learning resources in E-learning.Experiments show that the proposed algorithm can solve the problem of inaccurate and sparse data,and improves the quality of learning resources.关键词
协同过滤/学习行为/数据稀疏/隐式评分/相似度传递Key words
collaborative filtering/learning behavior/data sparsity/implicit rating/similarity propagation分类
信息技术与安全科学引用本文复制引用
付芬,豆育升,韩鹏,李耀辉..基于隐式评分和相似度传递的学习资源推荐[J].计算机应用研究,2017,34(12):3725-3729,5.基金项目
重庆市科技研发基地能力提升项目(cstc2014pt-gc40004) （cstc2014pt-gc40004）
