Home ›
Entities
› academia
› Extracting and summarizing affective features and responses from online product descriptions and reviews: A Kansei text mining approach
Extracting and summarizing affective features and responses from online product descriptions and reviews: A Kansei text mining approach
Research article (Engineering Applications of Artificial Intelligence, 2018) · cited 132× · AI/ML
Extracting and summarizing affective features and responses from online product descriptions and reviews: A Kansei text mining approach
Summary
Extracting and summarizing affective features and responses from online product descriptions and reviews: A Kansei text mining approach is a scholarly article[1].
Key Facts
Extracting and summarizing affective features and responses from online product descriptions and reviews: A Kansei text mining approach's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Extracting and summarizing affective features and responses from online product descriptions and reviews: A Kansei text mining approach. Retrieved May 24, 2026, from https://4ort.xyz/entity/extracting-and-summarizing-affective-features-and-responses-from-online-product-descriptions-and-reviews-a-kansei-text-m
MLA“Extracting and summarizing affective features and responses from online product descriptions and reviews: A Kansei text mining approach.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/extracting-and-summarizing-affective-features-and-responses-from-online-product-descriptions-and-reviews-a-kansei-text-m.
BibTeX@misc{4ortxyz_extracting-and-summarizing-affective-features-and-responses-from-online-product-descriptions-and-reviews-a-kansei-text-m_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Extracting and summarizing affective features and responses from online product descriptions and reviews: A Kansei text mining approach}}, year = {2026}, url = {https://4ort.xyz/entity/extracting-and-summarizing-affective-features-and-responses-from-online-product-descriptions-and-reviews-a-kansei-text-m}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Extracting and summarizing affective features and responses from online product descriptions and reviews: A Kansei text mining approach — https://4ort.xyz/entity/extracting-and-summarizing-affective-features-and-responses-from-online-product-descriptions-and-reviews-a-kansei-text-m (retrieved 2026-05-24)
