Modelling the sensory space of varietal wines : mining of large, unstructured text data and visualisation of style patterns
Date
2018
Journal Title
Journal ISSN
Volume Title
Publisher
Nature Publishing Group
Abstract
The increasingly large volumes of publicly available sensory descriptions of wine raises the question whether this source of data can be mined to extract meaningful domain-specific information about the sensory properties of wine. We introduce a novel application of formal concept lattices, in combination with traditional statistical tests, to visualise the sensory attributes of a big data set of some 7,000 Chenin blanc and Sauvignon blanc wines. Complexity was identified as an important driver of style in hereto uncharacterised Chenin blanc, and the sensory cues for specific styles were identified. This is the first study to apply these methods for the purpose of identifying styles within varietal wines. More generally, our interactive data visualisation and mining driven approach opens up new investigations towards better understanding of the complex field of sensory science.
Description
CITATION: Valente, C. C., et al. 2018. Modelling the sensory space of varietal wines : mining of large, unstructured text data and visualisation of style patterns. Scientific Reports, 8:4987, doi:10.1038/s41598-018-23347-w.
The original publication is available at http://www.nature.com
Publication of this article was funded by the Stellenbosch University Open Access Fund.
The original publication is available at http://www.nature.com
Publication of this article was funded by the Stellenbosch University Open Access Fund.
Keywords
Wine and wine making, Sensory properties of wine
Citation
Valente, C. C., et al. 2018. Modelling the sensory space of varietal wines : mining of large, unstructured text data and visualisation of style patterns. Scientific Reports, 8:4987, doi:10.1038/s41598-018-23347-w