Exploring students eating habits through individual profiling and clustering analysis
Natilli M., Monreale A., Guidotti R., Pappalardo L.
Food analytics Individual models Clustering analysis
Individual well-being strongly depends on food habits, therefore it is important to educate the general population, and especially young people, to the importance of a healthy and balanced diet. To this end, understanding the real eating habits of people becomes fundamental for a better and more effective intervention to improve the students' diet. In this paper we present two exploratory analyses based on centroid-based clustering that have the goal of understanding the food habits of university students. The first clustering analysis simply exploits the information about the students' food consumption of specific food categories, while the second exploratory analysis includes the temporal dimension in order to capture the information about when the students consume specific foods. The second approach enables the study of the impact of the time of consumption on the choice of the food.
Source: PAP 2018 - The 2nd International Workshop on Personal Analytics and Privacy, pp. 156–171, Dublin, Ireland, 10-14 September 2018
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@inproceedings{oai:it.cnr:prodotti:417426,
title = {Exploring students eating habits through individual profiling and clustering analysis},
author = {Natilli M. and Monreale A. and Guidotti R. and Pappalardo L.},
doi = {10.1007/978-3-030-13463-1_12},
booktitle = {PAP 2018 - The 2nd International Workshop on Personal Analytics and Privacy, pp. 156–171, Dublin, Ireland, 10-14 September 2018},
year = {2019}
}
0000-0002-2827-7613
