收稿日期: 2013-03-29
修回日期: 2013-07-01
网络出版日期: 2014-03-15
基金资助
Supported by National Natural Science Foundation of China(61103131/F020511)
A novel academic recommendation model with singular value decomposition and dynamic transfer chain
Received date: 2013-03-29
Revised date: 2013-07-01
Online published: 2014-03-15
Supported by
Supported by National Natural Science Foundation of China(61103131/F020511)
罗铁坚 , 程福兴 , 周佳 . 融合奇异值分解和动态转移链的学术资源推荐模型[J]. 中国科学院大学学报, 2014 , 31(2) : 257 -266 . DOI: 10.7523/jssn.2095-6134.2014.02.017
In the field of academic recommendation, changes in learner's preferences and academic trends with time affect the accuracy of academic recommendation systems. Most of the existing recommendation methods do not consider the time factor. We propose the dynamic transfer chain (DTC) to model users' preferences and academic trends over time. Based on DTC framework, we present a novel temporal academic recommendation algorithm (SVD&DTC) which combines singular value decomposition (SVD) and DTC together. Finally, we evaluate the effectiveness of the method using datasets on SeekSearch, and the results show a 3.89% improvement over the previous start-of-the-art.
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