Title: An intelligent recommendation method of remote ideological and political education resources based on user clustering

Authors: Yuan Zhang

Addresses: School of Political Science and Law and Public Administration, Yan'an University, Yan'an 716000, Shaanxi, China

Abstract: Aiming at the remote ideological and political education resources, due to the problems of low recall, poor recommendation effect and long recommendation time in traditional methods, a new intelligent recommendation method is proposed. First, user behaviour data with HTML5 and JavaScript technology were collected, and then filtering, dimension reduction, redundancy elimination and missing completion operations on the collected data were implemented. Then, users were modelled through the FBP model and user similarity was calculated. Finally, users with similar preferences were clustered using k-means++algorithm, the class of target users was searched, a scoring prediction matrix was established, and the highest scoring remote ideological and political education resources to users were recommended. The experimental results show that the proposed method cannot improve the recommendation accuracy and recall, but also shorten the recommendation time.

Keywords: user clustering; distance ideological; political education; user similarity; k-means++algorithm; scoring prediction matrix.

DOI: 10.1504/IJBIDM.2024.137729

International Journal of Business Intelligence and Data Mining, 2024 Vol.24 No.3/4, pp.340 - 351

Received: 22 Nov 2022
Accepted: 07 Mar 2023
Published online: 04 Apr 2024 *

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