Predicting and Visualizing Wine Characteristics Through Analysis of Tasting Notes from Viewpoints

  • Brendan FlanaganEmail author
  • Nao Wariishi
  • Takahiko Suzuki
  • Sachio Hirokawa
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 528)


When describing complex characteristics of a specific genre, specialist expressions are often used. This can become quite a problematic situation for an inexperienced person, as expressions not used in everyday language are difficult to understand. This is particularly apparent when trying to describe wines, known as winespeak, as a range of specialist expressions are used in a subjective manner. In this paper, we propose that the descriptions of wines can be analyzed from various points of view to automatically predict and visualize the sensory sentiment characteristics described within the expressions as a radar chart. This would enable those not knowledgeable in winespeak to visualize and compare the complex descriptions often found in expert tasting notes.


Support Vector Machine Feature Vector Support Vector Machine Classifier Support Vector Machine Model Sentiment Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was partially supported by JSPS KAKENHI Grant Number 24500176.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Brendan Flanagan
    • 1
    Email author
  • Nao Wariishi
    • 2
  • Takahiko Suzuki
    • 3
  • Sachio Hirokawa
    • 3
  1. 1.Graduate School of Information Science and Electrical EngineeringKyushu UniversityFukuokaJapan
  2. 2.Department of Electrical Engineering and Computer ScienceKyushu UniversityFukuokaJapan
  3. 3.Research Institute for Information TechnologyKyushu UniversityFukuokaJapan

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