CLJan 29, 2023
Syrupy Mouthfeel and Hints of Chocolate -- Predicting Coffee Review Scores using Text Based Sentiment
arXiv:2301.12417v11 citationsh-index: 3
Originality Synthesis-oriented
AI Analysis
This addresses a domain-specific problem for coffee industry stakeholders, but it is incremental as it applies existing methods to new data.
The paper tackled predicting coffee review scores (0-100) from specialized textual data in certified reviews, achieving accurate regression models that capture score patterns.
This paper uses textual data contained in certified (q-graded) coffee reviews to predict corresponding scores on a scale from 0-100. By transforming this highly specialized and standardized textual data in a predictor space, we construct regression models which accurately capture the patterns in corresponding coffee bean scores.