Bag-of-Foods: Analysis of Personal Foodlogging Data

Abstract

Food has great influence on our health, but at the same time it delights us. Food plays complexed role in our life because of these different aspects, thus dietary preferences should clearly show one's characteristics. However, since large food-intake record dataset was not obtained, very few researches have attacked analyzing people's dietary preferences statistically. Today, recording food-intake, or foodlogging, is becoming popular. There are several services help people do foodlogging in easier process, which enables us to gain access to the large foodlog dataset. In this paper, we focus on analysis of dietary preferences based on nutrition intake using foodlog dataset. We have found that clustering people by average nutrition intake per one meal gives fair result, which proves analyzing preference by nutrition as fair approach. We have also proposed a Bag-of-Words based method, Bag-of-Foods, to represent one's dietary preference feature, and shown that it certainly represents users' preference with richer expression than nutrition itself.

Cite

Text

Goda et al. "Bag-of-Foods: Analysis of Personal Foodlogging Data." International Joint Conference on Artificial Intelligence, 2018. doi:10.1145/3230519.3230596

Markdown

[Goda et al. "Bag-of-Foods: Analysis of Personal Foodlogging Data." International Joint Conference on Artificial Intelligence, 2018.](https://mlanthology.org/ijcai/2018/goda2018ijcai-bag/) doi:10.1145/3230519.3230596

BibTeX

@inproceedings{goda2018ijcai-bag,
  title     = {{Bag-of-Foods: Analysis of Personal Foodlogging Data}},
  author    = {Goda, Yuji and Amano, Sosuke and Yamakata, Yoko and Aizawa, Kiyoharu},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2018},
  pages     = {63-66},
  doi       = {10.1145/3230519.3230596},
  url       = {https://mlanthology.org/ijcai/2018/goda2018ijcai-bag/}
}