With the rising incidence of some diseases, such as obesity and diabetes, the healthy diet is arousing increasing attention. However, most existing food-related research efforts focus on recipe retrieval, user-preference-based food recommendation, cooking assistance, or the nutrition and calorie estimation of dishes, ignoring the personalized health-aware food recommendation. Therefore, in this work, we present a personalized health-aware food recommendation scheme, namely, Market2Dish, mapping the ingredients displayed in the market to the healthy dishes eaten at home. The proposed scheme comprises three components, namely, recipe retrieval, user health profiling, and health-aware food recommendation. In particular, recipe retrieval aims to acquire the ingredients available to the users and then retrieve recipe candidates from a large-scale recipe dataset. User health profiling is to characterize the health conditions of users by capturing the textual health-related information crawled from social networks. Specifically, to solve the issue that the health-related information is extremely sparse, we incorporate a word-class interaction mechanism into the proposed deep model to learn the fine-grained correlations between the textual tweets and pre-defined health concepts. For the health-aware food recommendation, we present a novel category-aware hierarchical memory network–based recommender to learn the health-aware user-recipe interactions for better food recommendation. Moreover, extensive experiments demonstrate the effectiveness of the health-aware food recommendation scheme.

中文翻译：

---

Market2Dish：健康食品推荐

随着肥胖、糖尿病等一些疾病的发病率不断上升，健康饮食越来越受到人们的重视。然而，现有的大多数与食物相关的研究工作都集中在食谱检索、基于用户偏好的食物推荐、烹饪辅助或菜肴的营养和卡路里估计上，而忽略了个性化的健康意识食物推荐。因此，在这项工作中，我们提出了一个个性化的健康意识食品推荐方案，即 Market2Dish，将市场上展示的食材映射到家里吃的健康菜肴。所提出的方案包括三个部分，即食谱检索、用户健康分析和健康感知食物推荐。特别是，食谱检索旨在获取用户可用的成分，然后从大规模食谱数据集中检索候选食谱。用户健康分析是通过捕获从社交网络爬取的文本健康相关信息来表征用户的健康状况。具体来说，为了解决与健康相关的信息极其稀疏的问题，我们在所提出的深度模型中加入了词类交互机制，以学习文本推文和预定义健康概念之间的细粒度相关性。对于健康感知食品推荐，我们提出了一种新颖的基于类别感知分层记忆网络的推荐器来学习健康感知用户与食谱的交互，从而获得更好的食物推荐。而且，