A collaborative filtering recommendation algorithm with time context for learning interest mining

被引：0
|
作者：
机构：
[1] School of Computer Science, Beijing University of Posts and Telecommunications, Beijing
来源：
| 1600年 / Beijing University of Posts and Telecommunications卷 / 37期
关键词：
Collaborative filtering; Learning interest mining; Recommender system; Time context;
D O I：
10.13190/j.jbupt.2014.06.010
中图分类号：
学科分类号：
摘要：
A time context based collaborative filtering recommendation (TCCF-LI) algorithm this paper was proposed, and students' learning interest mining from university library borrow record was implemented. The time context information was imported into the traditional collaborative filtering recommendation algorithm, in which, both interest homoplasy of large scale user groups and short-term correlation of small scale user groups was considered. Good recommendation performance was gained. According to the experiments on real dataset, TCCF-LI algorithm presents higher precision and recall rate compared with traditional recommendation algorithm. ©, 2014, Beijing University of Posts and Telecommunications. All right reserved.
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页码：49 / 53
页数：4
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