智能空间中的用户饮食偏好获取与推荐系统

摘要

This paper studies the user diet preferences acquisition techonology, and establishes a food category model based on similarity. It designs a system of user diet preferences acquisition and diet recommendation in smart space. The system uses pressure sensors to gain user's diet data, and captures user diet preferences by dynamic partition of sensor data. It uses the food category model to relize the diet recommendation. Experimental results proves the validity of the system.%对用户饮食偏好获取技术进行研究,建立基于相似度的食物分类模型,在此基础上设计智能空问中的用户饮食偏好获取及饮食推荐系统.该系统通过压力传感器采集用户饮食数据,利用动态分割数据的方法获取用户饮食偏好上下文,根据食物分类模型进行饮食推荐.实验结果证明了该系统的有效性.