Personalized Recommendation System for Offline Shopping

被引：0
|
作者：
Li, Pengbo [1 ]
Zhang, Guisong [2 ]
Chao, Li [1 ]
Xie, Zhifeng [1 ,2 ]
机构：
[1] Shanghai Univ, Shanghai Engn Res Ctr Mot Picture Special Effects, Shanghai, Peoples R China
[2] Shanghai Univ, Dept Film & Televis Engn, Shanghai, Peoples R China
来源：
2018 INTERNATIONAL CONFERENCE ON AUDIO, LANGUAGE AND IMAGE PROCESSING (ICALIP) | 2018年
基金：
中国国家自然科学基金;
关键词：
recommendation system; offline recommendation; data analysis; personalized;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper studies and establishes a system for the problem of lack of personalized commodity recommendation and low pertinence in shopping offline. Compared with online recommendation, offline system has inherent disadvantages on data. This paper overcomes its difficulties and does a further analysis and research on shopping information and commodity image of offline stores, and the algorithm model for offline personalized intelligent recommendation system was established, then the system was constructed to demonstrate its practicability and feasibility. Finally, we described the future of offline intelligent recommendation system and the difficulties to be solved, also we provide a promising outlook.
引用
收藏
页码：445 / 449
页数：5
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