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Paper Abstract and Keywords
Presentation 2018-02-15 13:15
Prediction and Evaluation of Long-Term Food Records Using Short-Term Food Records
Akihiro Tsubakida, Sosuke Amano, Yoko Yamakata, Kiyoharu Aizawa (UTokyo), Makoto Ogawa (foo.log Inc)
Abstract (in Japanese) (See Japanese page) 
(in English) In order to maintain and improve health, it is very important to grasp one's eating habits in his/her everyday life. However, it is not easy for an individual to continuously record his/her dishes in the long term. In this paper, we propose a method to predict individual long-term food records only by short-term records, and aim to grasp one's eating habits. In order to estimate the number of times the user ate each meal, we proposed a collaborative filtering considering time property and personality. In experiments, we improved an accuracy of RMSE by 10.8% compared with a baseline.
Keyword (in Japanese) (See Japanese page) 
(in English) food / eating habits / food records / collaborative filtering / / / /  
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Conference Information
Committee ITS IE ITE-MMS ITE-HI ITE-ME ITE-AIT  
Conference Date 2018-02-15 - 2018-02-16 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Image Processing, etc. 
Paper Information
Registration To ITE-ME 
Conference Code 2018-02-ITS-IE-MMS-HI-ME-AIT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Prediction and Evaluation of Long-Term Food Records Using Short-Term Food Records 
Sub Title (in English)  
Keyword(1) food  
Keyword(2) eating habits  
Keyword(3) food records  
Keyword(4) collaborative filtering  
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1st Author's Name Akihiro Tsubakida  
1st Author's Affiliation The University of Tokyo (UTokyo)
2nd Author's Name Sosuke Amano  
2nd Author's Affiliation The University of Tokyo (UTokyo)
3rd Author's Name Yoko Yamakata  
3rd Author's Affiliation The University of Tokyo (UTokyo)
4th Author's Name Kiyoharu Aizawa  
4th Author's Affiliation The University of Tokyo (UTokyo)
5th Author's Name Makoto Ogawa  
5th Author's Affiliation foo.log Inc (foo.log Inc)
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Speaker Author-1 
Date Time 2018-02-15 13:15:00 
Presentation Time 15 minutes 
Registration for ITE-ME 
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Volume (vol) vol.117 
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