Research on Personalized Hybrid Recommendation Method of Commodity Based on Context

被引：0

作者：

Lv ShanGuo ^{[1
]}

机构：

[1] East China Jiaotong Univ, Software Sch, Nanchang, Jiangxi, Peoples R China

来源：

2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND ENGINEERING (CSE) AND IEEE/IFIP INTERNATIONAL CONFERENCE ON EMBEDDED AND UBIQUITOUS COMPUTING (EUC), VOL 1 | 2017年

关键词：

hybrid personalized recommendation; Context; Data Sparsity; Collaborative Filtering Recommendation;

D O I：

10.1109/CSE-EUC.2017.111

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The design of recommendation method is the core of personalized recommendation, and the implementation of recommendation depends on the matching relation between user preference and resource object. This paper proposes a hybrid personalized recommendation method based on context-based collaborative filtering and knowledge recommendation, which is based on personalized recommendation knowledge model, from the view of user's attribute preference and user rating. Finally, the effectiveness of the method is proved by experiments.

引用

页码：607 / 610

页数：4

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