ArticleFrontiers in psychology2022
Human-computer interaction emotional design and innovative cultural and creative product design.
Article in Frontiers in psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- A hybrid method for assessing the perceived cultural value of cultural and creative products in e-commerce visual-textual presentation.Scientific reports · 2026Article
- Beyond usability: how AI tools shape design innovation ability among Chinese industrial design students.Frontiers in psychology · 2026Article
- Research on product design priority allocation based on user characteristics classification.Scientific reports · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
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Abstract
To make the interface design of computer application system better, meet the psychological and emotional needs of users, and be more humanized, the emotional factor is increasingly valued by interface designers. In the design of human-computer interaction graphical interfaces, the designer attaches great importance to the emotional design of the interface, and enhances the humanized design of the interface, which cannot only improve the comfort of the interface, but also improve the fun of the interface, to ensure the psychological and emotional needs of users can be better satisfied. It may acquire information that is favorable to innovative design by utilizing cluster analysis algorithm to tackle the problem of complicated cultural information, and then utilize cellular genetic algorithm to carry out creative design of cultural items. It increases the availability of cultural and creative goods. The classic cluster analysis technique offers the maximum data clustering effect of 53.3%, according to the findings of this paper's experiments. While the improved cluster analysis algorithm has the highest data clustering effect of 90%. It can be seen that the improved cluster analysis algorithm can effectively perform cluster analysis on a large amount of data in cultural and creative products. It thus finds out the most suitable designer's creative information, which helps designers create better products.
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