Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/10029

TitleModeling wine preferences by data mining from physicochemical properties
Author(s)Cortez, Paulo
Cerdeira, António
Almeida, Fernando
Matos, Telmo
Reis, José
KeywordsSensory preferences
Regression
Variable selection
Model selection
Suppor vector machines
Neural networks
Support vector machines
Issue dateNov-2009
PublisherElsevier
JournalDecision Support Systems
Citation"Decision Support Systems." ISSN 0167-9236. 47:4 (Nov. 2009) 547-553.
Abstract(s)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, un- der a computationally efficient procedure that performs simultaneous variable and model selection. The support vector machine achieved promising results, outper- forming 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.
TypeArticle
URIhttp://hdl.handle.net/1822/10029
DOI10.1016/j.dss.2009.05.016
ISSN0167-9236
Publisher versionhttp://dx.doi.org/10.1016/j.dss.2009.05.016
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CAlg - Artigos em revistas internacionais/Papers in international journals
DSI - Engenharia da Programação e dos Sistemas Informáticos

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