Abstract
According to the different objects concerned in collaborative filtering recommendation algorithm, it is divided into user-based and item-based collaborative filtering recommendation algorithm. This article analyzes and designs two algorithms according to the principle and recommendation functions. And can analyses the users’ potential consumer markets by applying these collaborative filtering recommendation algorithms in vertical e-commerce malls. The results show that the effect of collaborative filtering algorithm is obvious, and it has good performance compared with traditional algorithms.
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Acknowledgement
This paper is supported by the Dongguan social science and technology development (key) project, ID: 2020507151144. This work is supported by Key Field Special Project of Guangdong Provincial Department of Education with No. 2021ZDZX1029.
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Shen, J., Zhu, T. (2022). Algorithm of Collaborative Filtering Recommendation and Its Application in Electronic Shopping Mall. In: Li, K., Liu, Y., Wang, W. (eds) Exploration of Novel Intelligent Optimization Algorithms. ISICA 2021. Communications in Computer and Information Science, vol 1590. Springer, Singapore. https://doi.org/10.1007/978-981-19-4109-2_47
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DOI: https://doi.org/10.1007/978-981-19-4109-2_47
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