Furniture Design Methods Based on Online Comment Relationship Extraction

LU Jintong; LIN Qiuli; GENG Rui; SONG Jie; GUO Qiong; FANG Xiaoya

doi:10.19554/j.cnki.1001-3563.2026.04.003

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Packaging Engineering ›› 2026, Vol. 47 ›› Issue (4) : 30-38. DOI: 10.19554/j.cnki.1001-3563.2026.04.003

Industrial Design

Furniture Design Methods Based on Online Comment Relationship Extraction

LU Jintong¹, LIN Qiuli², GENG Rui³, SONG Jie⁴, GUO Qiong^4,*, FANG Xiaoya¹

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Abstract

In response to the problems of small sample size, strong subjectivity, low efficiency, and fuzzy mapping in traditional sensory evaluation methods, the work aims to propose a sensory evaluation element recognition method based on CasRel relation extraction model and emotion dictionary to accurately mine users' emotional needs for furniture products. The feature descriptions and user evaluations of relevant products were widely collected through the Internet platform, and representative words were extracted by text mining technology and weight screening methods. On this basis, a relationship extraction model was constructed and trained to establish an "emotion-feature" automatic association system. The effectiveness of the model was validated through practical cases and the design optimization was guided. The trained model could efficiently and accurately identify the correspondence between user emotions and product features from a large number of comments, verifying the practical value of the method. The online comment relationship extraction method can efficiently mine user needs, provide data-driven decision support for furniture design, and significantly improve design efficiency and accuracy.

Key words

sensory evaluation / Kansei engineering / online product comment / relationship extraction / neural network

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LU Jintong, LIN Qiuli, GENG Rui, SONG Jie, GUO Qiong, FANG Xiaoya. Furniture Design Methods Based on Online Comment Relationship Extraction[J]. Packaging Engineering. 2026, 47(4): 30-38 https://doi.org/10.19554/j.cnki.1001-3563.2026.04.003

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