Very quaffable and great fun: Applying NLP to wine reviews
作者: Iris Hendrickx, Els Lefever, Ilja Croijmans, Asifa Majid, Antal van den Bosch
摘要
People find it difficult to name odors and flavors. In blind tests with everyday smells and tastes like orange or chocolate, only 50% is recognized and described correctly. Certain experts like wine reviewers are trained in recognizing and reporting on odor and flavor on a daily basis and they have a much larger vocabulary than lay people. In this research, we want to examine whether expert wine tasters provide consistent descriptions in terms of perceived sensory attributes of wine, both across various wine types and colors. We collected a corpus of wine reviews and performed preliminary experiments to analyse the semantic fields of „flavor” and „odor” in wine reviews. To do so, we applied distributional methods as well as pattern-based approaches. In addition, we show the first results of automatically predicting „color” and „region” of a particular wine, solely based on the reviewer’s text. Our classifiers perform very well when predicting red and white wines, whereas it seems more challenging to distinguish rose wines.