Abstract
In this paper, we propose a support system for healthy eating habits. Current methods of recipe retrieval generally rely on keywords or popularity. However, such approaches offer the same results to different users. In order to resolve this issue, we have developed a support system that incorporates nutritional management and preferential retrieval. In the preferential retrieval system, a recommender agent takes account of user tastes to extract and present menus. The user then, evaluates the menus recommended by various agents. Each recommender agents evolves on the basis of these menu appraisals. Over time, the preferences of the agents become similar to those of the users, resulting in menus that correspond to user tastes. This study thus utilizes an interactive immune algorithm (IIA) to optimize the preferential retrieval system. We tested the proposed system with a simulated user but genuine recipe data.
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Inagawa, Y., Hakamta, J., Tokumaru, M. (2013). A Support System for Healthy Eating Habits: Optimization of Recipe Retrieval. In: Stephanidis, C. (eds) HCI International 2013 - Posters’ Extended Abstracts. HCI 2013. Communications in Computer and Information Science, vol 374. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39476-8_35
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DOI: https://doi.org/10.1007/978-3-642-39476-8_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39475-1
Online ISBN: 978-3-642-39476-8
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