Title
Characterizing and Predicting Repeat Food Consumption Behavior for Just-in-Time Interventions
Abstract
Human beings are creatures of habit. In their daily life, people tend to repeatedly consume similar types of food items over several days and occasionally switch to consuming different types of items when the consumptions become overly monotonous. However, the novel and repeat consumption behaviors have not been studied in food recommendation research. More importantly, the ability to predict daily eating habits of individuals is crucial to improve the effectiveness of food recommender systems in facilitating healthy lifestyle change. In this study, we analyze the patterns of repeat food consumptions using large-scale consumption data from a popular online fitness community called MyFitnessPal (MFP), conduct an offline evaluation of various state-of-the-art algorithms in predicting the next-day food consumption, and analyze their performance across different demographic groups and contexts. The experiment results show that algorithms incorporating the exploration-and-exploitation and temporal dynamics are more effective in the next-day recommendation task than most state-of-the-art algorithms.
Year
DOI
Venue
2019
10.1145/3357729.3357736
Proceedings of the 9th International Conference on Digital Public Health
Keywords
Field
DocType
food recommendation, implicit feedback, repeat consumption
Food consumption,Psychological intervention,Psychology,Environmental health
Conference
ISBN
Citations 
PageRank 
978-1-4503-7208-4
1
0.36
References 
Authors
0
6
Name
Order
Citations
PageRank
Yue Liu144184.32
Helena Lee210.36
Palakorn Achananuparp330223.16
Ee-Peng Lim45889754.17
Tzu-Ling Cheng510.36
Shou-De Lin670684.81