Research on real-time personalized recommendation algorithm

被引：0
|
作者：
Lijun, Liu [1 ]
机构：
[1] Department of Logistics Information, Hunan Vocational College of Modern Logistics, Changsha, China
来源：
International Journal of u- and e- Service, Science and Technology | 2014年 / 7卷 / 05期
关键词：
Personalized recommendation - Quality of recommendations - Real- time - Recommendation algorithms - Slope ones - User groups - User interest model;
D O I：
10.14257/ijunnesst.2014.7.5.32
中图分类号：
学科分类号：
摘要：
Personalized recommendation algorithm is core to recommendation systems, which matters the quality of recommendations of such system. The paper proposed an improved Slope one recommendation algorithm, M-Slope one. Based on real-time user interest model, the new method can calculate similarities between users and establish neighboring user groups to narrow down search scope of related items and improve the average rating differential equation for items. The algorithm proves its effectiveness for improving the precision of recommendations. © 2014 SERSC.
引用
收藏
页码：359 / 368
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