Title: A study on the impact of personalised recommendation algorithms in webcasting on the development of rural e-commerce entrepreneurship

Authors: Jie Li

Addresses: School of Economics and Management, Fujian Vocational and Technical College of Water Conservancy and Electric Power, Yongan, 366000, China

Abstract: The vigorous development of rural e-commerce has brought a great positive effect on the development of rural economy and the improvement of local people's living material conditions. Among them, online live broadcasting provides a new perspective for the personalised development of e-commerce entrepreneurship. At the same time, based on the advantages of collaborative filtering (CF) algorithm in formulating user scoring criteria, the random forest (RF) algorithm is introduced to realise the research on the correlation of some features, so as to improve the information anti-noise ability and optimise the algorithm performance. And the intelligent recommendation algorithm that combines RF algorithm and improved CF algorithm is applied to rural e-commerce entrepreneurship recommendation. The results show that the fusion algorithm combines the advantages of the RF algorithm and the improved CF algorithm, which makes it have better performance in content recommendation.

Keywords: collaborative filtering; rural e-commerce; random forest; webcasting.

DOI: 10.1504/IJCSYSE.2023.132914

International Journal of Computational Systems Engineering, 2023 Vol.7 No.2/3/4, pp.135 - 145

Received: 30 Oct 2022
Accepted: 13 Mar 2023
Published online: 16 Aug 2023 *

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