ArticleScientific reports2018
Modelling the sensory space of varietal wines: Mining of large, unstructured text data and visualisation of style patterns.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Cultural differences in wine conceptualization among consumers in France, Portugal and South Africa.Scientific reports · 2024Article
- Prevalence of symptoms, comorbidities, fibrin amyloid microclots and platelet pathology in individuals with Long COVID/Post-Acute Sequelae of COVID-19 (PASC).Cardiovascular diabetology · 2022Article
- The Impact of "Wine Country of Origin" on the Perception of Wines by South African and French Wine Consumers: A Cross-Cultural Comparison.Foods (Basel, Switzerland) · 2021Article
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Authors and funding
5 authors.
Funding
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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.
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