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结合时间上下文挖掘学习兴趣的协同过滤推荐算法

DOI: 10.13190/j.jbupt.2014.06.010, PP. 49-53

Keywords: 推荐系统,协同过滤,时间上下文,学习兴趣挖掘

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Abstract:

提出了一种基于时间上下文的协同过滤推荐(TCCF-LI)算法,实现了基于高校图书馆图书借阅记录数据上的学生学习兴趣挖掘.在传统协同过滤算法上引入时间上下文信息,既考虑了大尺度用户群体爱好的趋同性,又兼顾了小尺度个体用户爱好的短时相关性,获得了更高的推荐性能.在实际数据集上的实验结果表明,该算法在推荐精准度、召回率等方面比传统推荐算法有较好表现.

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