For non-connoisseurs, picking out a bottle of wine can be challenging when scanning an array of unfamiliar labels on the shop shelf. What does it taste like? What was the last one I bought that tasted so good?
Here, wine apps like Vivino, Hello Vino, Wine Searcher and a host of others can help. Apps like these let wine buyers scan bottle labels and get information about a particular wine and read the reviews of others. These apps build upon artificially intelligent algorithms.
Now, scientists from the Technical University of Denmark (DTU), the University of Copenhagen and Caltech have shown that you can add a new parameter to the algorithms that makes it easier to find a precise match for your own taste buds: Namely, people’s impressions of flavour.
“We have demonstrated that, by feeding an algorithm with data consisting of people’s flavour impressions, the algorithm can make more accurate predictions of what kind of wine we individually prefer,” says Thoranna Bender, a graduate student at DTU who conducted the study under the auspices of the Pioneer Centre for AI at the University of Copenhagen.
More accurate predictions of people’s favourite wines
The researchers held wine tastings during which 256 participants were asked to arrange shot-sized cups of different wines on a piece of A3 paper based upon which wines they thought tasted most similarly. The greater the distance between the cups, the greater the difference in their flavour. The method is widely used in consumer tests. The researchers then digitized the points on the sheets of paper by photographing them.
The data collected from the wine tastings was then combined with hundreds of thousands of wine labels and user reviews provided to the researchers by Vivino, a global wine app and marketplace. Next, the researchers developed an algorithm based on the enormous data set.
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