Title: Study on evaluation method of human-computer interface quality of intelligent products based on Bayesian classification

Authors: Jinrong Li

Addresses: Department of Mathematics and Information Engineering, Puyang Vocational and Technical College, Hualong District, Puyang, China

Abstract: In order to improve the accuracy and efficiency of human-computer interaction interface quality evaluation, this paper proposes an intelligent product interaction interface quality evaluation method based on Bayesian classification. An adaptive Gauss filter is introduced to adjust the colour of intelligent product interaction interface through logarithmic operator, and the intelligent product interaction interface is formally described. Bayesian classification method is used to build the quality evaluation model of intelligent product interaction interface. According to Bayesian classification probability reasoning mechanism, the quality of intelligent product interaction interface is evaluated. According to the relevant verification results, the average significance of the proposed method is as high as 95.7%, the recognition accuracy is 96.4% and the evaluation time is only 7.2 s, which has a good evaluation effect.

Keywords: Bayesian classification; adaptive Gaussian filter; intelligent product; human-computer interaction interface; quality assessment.

DOI: 10.1504/IJPD.2024.137813

International Journal of Product Development, 2024 Vol.28 No.1/2, pp.24 - 34

Received: 29 Apr 2022
Accepted: 03 Oct 2022
Published online: 05 Apr 2024 *

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