Simultaneous Analysis of Subjective and Objective Data Using Coupled Tensor Self-organizing Maps: Wine Aroma Analysis with Sensory and Chemical Data

  • Keisuke Yoneda
  • Kimihiro Nakano
  • Keiichi Horio
  • Tetsuo FurukawaEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11306)


In this paper, we propose a method for simultaneous analysis of subjective and objective data. The method, named coupled tensor self-organizing map (SOM), consists of two tensor SOMs, one of which learns the subjective data while the other learns the objective data. The coupled tensor SOM visualizes the dataset as three maps, namely, one target object map, and two survey item maps corresponding to the subjective and objective data. This method can be further extended to generate extra maps such as a map of attributes. In addition, the coupled tensor SOM also provides an interactive visualization of the relationship between the target objects and the survey items by coloring these three maps. We applied our proposed method to the wine aroma dataset. Our results indicate that this method facilitates an intuitive overview of the dataset.


Subjective and objective data Multi-view data Coupled tensor decomposition Multi-relational data Tensor SOM Self-organizing map 


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Keisuke Yoneda
    • 1
  • Kimihiro Nakano
    • 2
  • Keiichi Horio
    • 1
  • Tetsuo Furukawa
    • 1
    Email author
  1. 1.Kyushu Institute of TechnologyKitakyushuJapan
  2. 2.Kuraray Co., Ltd.TokyoJapan

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