Research on personalized recommendation system on Item-based collaborative filtering algorithm
文献类型: 外文期刊
作者: Zhao, Ji-chun 1 ; Liu, Shi-hong 2 ; Zhang, Junfeng 3 ;
作者机构: 1.Beijing Acad Agr & Forestry Sci, Beijing, Peoples R China
2.Chinese Acad Agr Sci, Inst Agr Informat, Beijing 100193, Peoples R China
3.Res Ctr Beijing Engn technol Rural Remote Informa, Beijing, Peoples R China
关键词: Distance Learning;Item based collaborative filtering algorithm;Personalized Learning
期刊名称:PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ADVANCES IN MECHANICAL ENGINEERING AND INDUSTRIAL INFORMATICS
ISSN: 2352-5401
年卷期: 2015 年 15 卷
页码:
收录情况: SCI
摘要: A lot of learning resources and information occupy rural distance education platform, and farmers don't know how to find useful information in the learning platform. Personalized distance learning system can provide farmers with required learning resources. The paper analyzes classical collaborative filtering algorithms, and Item based collaborative filtering algorithm is used in distance education platform, which is experimented with the distance learning platform data. The test result show that item based collaborative filtering algorithm in prediction accuracy and coverage is better with the growing of the sparsity of the data set, and the average accuracy is82.99%, the average coverage is 99.06%.
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