Title: Prediction method of commercial customers' mental health based on data mining

Authors: Yanhua Shen; Bing Gao

Addresses: School of Public Administration, China University of Mining and Technology, Xuzhou, Jiangsu, 221116, China ' School of Public Administration, China University of Mining and Technology, Xuzhou, Jiangsu, 221116, China

Abstract: For commercial customer management, mental health prediction is crucial, therefore, a data mining-based method for predicting the mental health of commercial customers is proposed. Firstly, the K-means algorithm is used to mine and process the psychological health test data of commercial customers. Secondly, develop a program for evaluating the psychological health of commercial customers, construct a judgment matrix, and calculate weight coefficients to obtain the evaluation results of the psychological health level of commercial customers. Finally, based on the evaluation results of mental health level as input and the predicted results of mental health, a BP neural network is used to build a commercial customer mental health prediction model. The experimental data shows that after the proposed method is applied, the mining results of commercial customers' mental health data are consistent with the actual results, and the minimum error of commercial customers' mental health prediction is 0.4%.

Keywords: commercial customers; mental health; enterprise development; data mining technology; prediction model construction.

DOI: 10.1504/IJDMB.2025.142990

International Journal of Data Mining and Bioinformatics, 2025 Vol.29 No.1/2, pp.67 - 86

Received: 30 Jun 2023
Accepted: 26 Oct 2023
Published online: 02 Dec 2024 *

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