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Received:November 06, 2015 Revised:December 10, 2015
Received:November 06, 2015 Revised:December 10, 2015
中文摘要: 传统的选修课系统存在结构性的不足和缺憾,为了避免高校学生盲目的选择选修课程,本文利用改进的协同过滤算法对高校学生进行个性化的选课推荐.本文首先介绍了两种推荐算法,并着重介绍基于协同过滤的推荐算法,并分析了两种算法的优缺点,最后针对协同过滤算法的数据稀疏性问题,提出了一种改进的协同过滤算法,即在协同过滤中加入基于内容的因素来解决这个问题.这种改进的协同过滤算法避免了传统协同过滤算法中存在的数据稀疏问题,以学生为本推荐适合学生的课程,满足学生学习的个性化要求.
Abstract:Traditional elective system has structural deficiencies and defects. To avoid the fact that college students choose a course with blindness, therefore, with improved collaborative filtering algorithm, college students can get personalized elective course election. This paper first introduces two kinds of recommendation algorithms. Also the paper emphatically introduces recommendation algorithms based on collaborative filtering. It analyzes the advantages and disadvantages of the two algorithms. Finally, for data sparsity of collaborative filtering algorithm, it proposes an improved collaborative filtering algorithm, that adds factor in content-based collaborative filtering to solve this problem. Improved collaborative filtering algorithm avoids the traditional algorithms emerging data sparseness problem. Recommending appropriate courses for students on human-oriented, individual needs of students can be met.
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张亮,赵娜.改进的协同过滤推荐算法.计算机系统应用,2016,25(7):147-150
ZHANG Liang,ZHAO Na.Improved Collaborative Filtering Algorithm.COMPUTER SYSTEMS APPLICATIONS,2016,25(7):147-150
张亮,赵娜.改进的协同过滤推荐算法.计算机系统应用,2016,25(7):147-150
ZHANG Liang,ZHAO Na.Improved Collaborative Filtering Algorithm.COMPUTER SYSTEMS APPLICATIONS,2016,25(7):147-150