A comprehensive survey on recommender system techniques

被引：0

作者：

Ganesan, Thenmozhi ^{[1
]}

Jothi, R. Anandha ^{[1
]}

Vellaiyan, Palanisamy ^{[1
]}

机构：

[1] Department of Computer Applications, Alagappa University, Karaikudi,630003, India

来源：

International Journal of Computational Systems Engineering | 2023年 / 7卷 / 2-4期

关键词：

Classification (of information) - Collaborative filtering - Electronic commerce - Information services - Machine learning - Sales;

D O I：

10.1504/IJCSYSE.2023.132915

中图分类号：

学科分类号：

摘要：

The recommender system (RecSys) is a relatively emergent research area in machine learning that helps users to get personalised products, friends, documents, places and other online services with minimal time. RecSys has been proved as an important solution for information overload problems, by providing more proactive and personalised information services. It performs like a gateway for users to be recommended as to what decision would be right and predicts future post decision. RecSys utilised to support the venture to implement one-to-one marketing strategies in e-commerce. These strategies present enormous advantages namely satisfying the customer’s interest increase the possibility of cross-selling and demonstrating the customer loyalty. This paper presents the overview of recommender system approaches, applications and challenges and directly supports the researchers in their understanding of this field. Further, we surveyed collaborative filtering-based RecSys in detailed manner and scrutinised the strengths and limitations to assist the future researchers. © 2023 Inderscience Enterprises Ltd.

引用

页码：146 / 158