Yingchao Wang1, Yuanhao Zhu1, Zongtian Zhang1, Huihuang Liu1,* , Peng Guo2
Journal of New Media, Vol.3, No.4, pp. 119-128, 2021, DOI:10.32604/jnm.2021.016655
- 05 November 2021
Abstract In order to improve user satisfaction and loyalty on e-commerce
websites, recommendation algorithms are used to recommend products that may
be of interest to users. Therefore, the accuracy of the recommendation algorithm
is a primary issue. So far, there are three mainstream recommendation algorithms,
content-based recommendation algorithms, collaborative filtering algorithms and
hybrid recommendation algorithms. Content-based recommendation algorithms
and collaborative filtering algorithms have their own shortcomings. The contentbased recommendation algorithm has the problem of the diversity of
recommended items, while the collaborative filtering algorithm has the problem
of data sparsity and scalability. On the basis of More >
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