Modeling wine preferences by data mining from physicochemical properties

• Type: Article in International Scientific Journal
• Date: 2009

Authors

Cortez, P (Author) Other; Cerdeira, A (Author) Other; Almeida, F (Author) Other; Matos, T (Author) Other; Reis, J (Author) Other

Journal

Title: Decision Support Systems

Vol. 47

Pages: 547-553

ISSN: 0167-9236

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 586 Citations

Scopus - 713 Citations

Other information

Authenticus ID: P-003-EJ2

DOI: 10.1016/j.dss.2009.05.016

Abstract (EN): We propose a data mining approach to predict human wine taste preferences that is based on easily available analytical tests at the certification step. A large dataset (when compared to other studies in this domain) is considered, with white and red vinho verde samples (from Portugal). Three regression techniques were applied, under a computationally efficient procedure that performs simultaneous variable and model selection. The support vector machine achieved promising results, Outperforming the multiple regression and neural network methods. Such model is useful to support the oenologist wine tasting evaluations and improve wine production. Furthermore, similar techniques can help in target marketing by modeling consumer tastes from niche markets.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 7