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

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%.

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Publication Details

Journal
International Journal of Data Mining and Bioinformatics
Published
2024-12-03
DOI
https://doi.org/10.1504/ijdmb.2025.142990
Citations
1
Primary Topic
E-commerce and Technology Innovations
Type
article
Field-Weighted Citation Impact
0.68
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article

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

Bing Gao, Yanhua Shen
1 citations
International Journal of Data Mining and Bioinformatics
E-commerce and Technology Innovations
0.68
article

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

Bing Gao, Yanhua Shen
article en
1 citations

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%.

International Journal of Data Mining and BioinformaticsVol. 29(1/2)
China University of Mining and Technology (CN)
Openalex Percentile: Top 23%
E-commerce and Technology Innovations
0.68
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