Exploring the use of large language models to build product Kansei semantic spaces

• GPT-4 can produce semantic spaces equivalent to those of existing techniques. • Two different approaches have been tested with similar positive results. • The extended procedure considers GPT-4 variability, allowing for more varied terms. • The short procedure is faster and produce terms slightly closer to the product.

Authors

Institutions

Publication Details

Journal
International Journal of Industrial Ergonomics
Published
2025-03-17
DOI
https://doi.org/10.1016/j.ergon.2025.103709
Citations
1
Primary Topic
Color perception and design
Type
article
Field-Weighted Citation Impact
2.44
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploring the use of large language models to build product Kansei semantic spaces

Jorge Alcaide-Marzal, José Antonio Diego-Más
1 citations
International Journal of Industrial Ergonomics
Color perception and design
2.44
article

Exploring the use of large language models to build product Kansei semantic spaces

Jorge Alcaide-Marzal, José Antonio Diego-Más
article en
1 citations

Abstract

• GPT-4 can produce semantic spaces equivalent to those of existing techniques. • Two different approaches have been tested with similar positive results. • The extended procedure considers GPT-4 variability, allowing for more varied terms. • The short procedure is faster and produce terms slightly closer to the product.

International Journal of Industrial ErgonomicsVol. 107
Universitat Politècnica de València (ES)
Openalex Percentile: Top 15%
Color perception and design
2.44
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.