@inproceedings{c33c2a963e004b20b6e1f37f0f7b858b,
title = "{"}serving Each User{"}: Supporting different eating goals through a multi-list recommender interface",
abstract = "Food recommender systems optimize towards a user's current preferences. However, appetites may vary, in the sense that users might seek healthy recipes today and look for unhealthy meals tomorrow. In this paper, we propose a novel approach in the food domain to diversify recommendations across different lists to 'serve' different users goals, compiled in a multi-list food recommender interface. We evaluated our interface in a 2 (single list vs multiple lists) x 2 (without or with explanations) between-subject user study (N = 366), linking choice behavior and evaluation aspects through the user experience framework. Our multi-list interface was evaluated more favorably than a single-list interface, in terms of diversity and choice satisfaction. Moreover, it triggered changes in food choices, even though these choices were less healthy than those made in the single-list interface. ",
keywords = "Food, Goals, Health, Nudges, Recommender Systems, User Experience",
author = "Alain Starke and Edis Asotic and Christoph Trattner",
year = "2021",
month = sep,
day = "13",
doi = "10.1145/3460231.3474232",
language = "English",
series = "RecSys 2021 - 15th ACM Conference on Recommender Systems",
pages = "124--132",
booktitle = "RecSys 2021 - 15th ACM Conference on Recommender Systems",
note = "15th ACM Conference on Recommender Systems, RecSys 2021 ; Conference date: 27-09-2021 Through 01-10-2021",
}