Meal recommendation, as a typical health-related recommendation task, contains complex relationships between users, courses, and meals. Among them, meal-course affiliation associates user-meal and user-course interactions. However, an extensive literature review demonstrates that there is a lack of publicly available meal recommendation datasets including meal-course affiliation. Meal recommendation research has been constrained in exploring the impact of cooperation between two levels of interaction on personalization and healthiness. To pave the way for meal recommendation research, we introduce a new benchmark dataset called MealRec$^+$. Due to constraints related to user health privacy and meal scenario characteristics, the collection of data that includes both meal-course affiliation and two levels of interactions is impeded. Therefore, a simulation method is adopted to derive meal-course affiliation and user-meal interaction from the user's dining sessions simulated based on user-course interaction data. Then, two well-known nutritional standards are used to calculate the healthiness scores of meals. Moreover, we experiment with several baseline models, including separate and cooperative interaction learning methods. Our experiment demonstrates that cooperating the two levels of interaction in appropriate ways is beneficial for meal recommendations. Furthermore, in response to the less healthy recommendation phenomenon found in the experiment, we explore methods to enhance the healthiness of meal recommendations. The dataset is available on GitHub (https://github.com/WUT-IDEA/MealRecPlus).

翻译：餐饮推荐作为典型的健康相关推荐任务，涉及用户、菜品与餐品之间复杂的关联关系。其中，餐品-菜品隶属关系将用户-餐品交互与用户-菜品交互联系起来。然而，广泛文献综述表明，目前缺乏包含餐品-菜品隶属关系的公开餐饮推荐数据集。这限制了餐饮推荐研究在探索两类交互协同作用对个性化与健康性影响方面的进展。为推进餐饮推荐研究，我们提出名为MealRec$^+$的新型基准数据集。受限于用户健康隐私与餐饮场景特性，同时包含餐品-菜品隶属关系与两类交互的数据收集难以实现。因此，我们采用模拟方法，基于用户-菜品交互数据模拟用户就餐会话，进而推导餐品-菜品隶属关系与用户-餐品交互。随后，采用两种公认营养标准计算餐品健康得分。此外，我们实验了多种基线模型，包括独立与协同交互学习方法。实验表明，以适当方式协同两类交互有利于餐饮推荐。针对实验中发现的"不够健康"推荐现象，我们探索了提升餐饮推荐健康性的方法。该数据集已在GitHub上开源（https://github.com/WUT-IDEA/MealRecPlus）。