期刊名称：International Journal of Multimedia and Ubiquitous Engineering
印刷版ISSN：1975-0080
出版年度：2015
卷号：10
期号：4
页码：71-80
DOI：10.14257/ijmue.2015.10.4.08
出版社：SERSC
摘要：Recommendation algorithm is a kind of method in information filtering and has been widely applied on Internet. Collaborative filtering is widely used in the recommendation systems and has turned out to be successful. With the growth of the resources, it is difficult for users to find learning resources that suit for themselves. The recommendation algorithm is required to analyze the behavior of the users and then recommend object of learning. Online judge is a kind of the online learning. People can evaluate their programming ability through online judge. The performance of the different recommendation algorithms is analyzed in this paper and it is proposed that the item- based collaborative filtering recommendation algorithms should be applied into the online learning system. Based on the algorithm, we propose that by pre-processing the data and using user data that have solve large number of problems, we can get a better recommendation result.
