Development of a Nutritional Management System for a Healthy Eating Habits Support System
Yuta Tokumi*, Junki Hakamata*, and Masataka Tokumaru**
*Graduate School of Kansai University, 3-3-35 Yamate-cho, Suita-shi, Osaka 564-8680, Japan
**Kansai University, 3-3-35 Yamate-cho, Suita-shi, Osaka 564-8680, Japan
In this study, we propose a Nutritional Management System (NMS) that optimizes nutritional balance using a tabu search. Contemporary recipe retrieval systems generally retrieve a recipe either by using a keyword or by recommending a popular recipe. However, these recipe retrieval systems yield the same retrieval results for different users, and thus, the results do not necessarily reflect an individual user’s tastes. In addition, the search results delivered by many recipe retrieval systems do not always describe the nutritional details of the recipes. Therefore, we developed a Healthy Eating Habits Support System for resolving these issues. This system is composed of an NMS and a Kansei Retrieval System (KRS). The NMS retrieves nutritionally balanced menus using a tabu search. The KRS learns a user’s taste preferences, and selects menus suitable for a user’s tastes from among the menus retrieved by the NMS. The KRS needs multiple nutritionally balanced menus to learn a user’s taste preferences. Thus, in this study, we simulated scenarios to examine whether the NMS can retrieve multiple nutritionally balanced menus in the long-term without duplication, using quasi recipe data and real recipe data. When we used quasi recipe data in a simulation with a very large number of recipes, the NMS could retrieve a sustained quantity of menus in the long-term. In addition, when we used real recipe data, the NMS could quickly retrieve menus over the long-term. Therefore, the effectiveness of the NMS was confirmed.
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