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Title: Vocational college employment training and career planning model design based on improved collaborative filtering

Authors: Jin Wang

Addresses: Department of Tourism Management, Yellow River Conservancy Technical Institute, Kaifeng, 475004, China

Abstract: In the manuscript, a vocational college student employment training and career planning model based on collaborative filtering is proposed to recommend suitable employment training and career planning for students. Focusing on the flaws of collaborative filtering algorithm in data mining of students' employment behaviour, the K-means clustering algorithm and Kruskal are combined to optimise it. The experiment is conducted using the employment data of vocational school graduates in the past three years. The outcomes indicate that the accuracy of this model reaches 94.18%, which is 2.93% and 2.12% higher than that of CF and KCF respectively. It proves that this method can basically meet the career planning and vocational training needs of vocational school students in the employment process, establishing a good connection between students and enterprises.

Keywords: vocational colleges; employment training; career planning; collaborative filtering; Kruskal algorithm.

DOI: 10.1504/IJCSYSE.2025.148029

International Journal of Computational Systems Engineering, 2025 Vol.9 No.13, pp.1 - 10

Received: 12 Apr 2023
Accepted: 22 Jul 2023
Published online: 15 Aug 2025 *