Research on Children's Furniture Design Routes Oriented by Online Review Texts
To explore extensive and authentic user needs and analyze their significance scientifically,this study employs online review texts integrated with F-Kano/AHP/TOPSIS models to conduct user requirement analysis for children's furniture design.Python crawler technology was used to collect online review data from e-commerce platforms,forming an initial corpus,with Jieba segmentation applied to extract product characteristics.F-Kano was then employed for attribute analysis to categorize user needs,while AHP was utilized to construct a hierarchical analysis model and calculate weights.Finally,the TOPSIS method objectively evaluated the design schemes,validating the research approach.This method leverages reliable user input from online reviews and integrates F-Kano/AHP/TOPSIS to enhance user satisfaction and market competitiveness for children's furniture,offering a valuable reference for similar product design.