个人食品模型
Personal Food Model
摘要：
食物是生活的中心。食物为我们的身体提供能量和基础构件，也是快乐和新体验的主要来源。整体经济的很大一部分与粮食有关。食品科学、分配、加工和消费已经由不同的社区使用计算方法的筒仓来解决。在本文中，我们采用了以人为中心的多媒体和多模态的角度来看待食品计算，并展示了多媒体和食品计算如何协同和互补。享受食物是一种真正的多媒体体验，涉及视觉，味觉，嗅觉，甚至声音，可以使用多媒体食物记录器捕获。可以使用可用的可穿戴设备使用多模态数据流来捕获对食物的生物反应。这种方法的核心是个人食物模式。个人食物模型是个人食物相关特征的数字化表示。它被设计用于食物推荐系统，以提供与饮食相关的建议，提高用户的生活质量。为了模拟每个人与食物相关的特征，必须使用偏好个人食物模型来捕捉他们与食物相关的享受，并使用他们的生物个人食物模型来捕捉他们对食物的生物反应。受三维颜色模型视觉处理能力的启发，我们引入了一个6维味觉空间，用于捕捉烹饪特征和个人偏好。我们使用事件挖掘方法将食物与其他生活和生物事件联系起来，以建立一个预测模型，该模型也可以有效地用于新兴的食物推荐系统。
英文摘要：
Food is central to life. Food provides us with energy and foundational building blocks for our body and is also a major source of joy and new experiences. A significant part of the overall economy is related to food. Food science, distribution, processing, and consumption have been addressed by different communities using silos of computational approaches. In this paper, we adopt a person-centric multimedia and multimodal perspective on food computing and show how multimedia and food computing are synergistic and complementary. Enjoying food is a truly multimedia experience involving sight, taste, smell, and even sound, that can be captured using a multimedia food logger. The biological response to food can be captured using multimodal data streams using available wearable devices. Central to this approach is the Personal Food Model. Personal Food Model is the digitized representation of the food-related characteristics of an individual. It is designed to be used in food recommendation systems to provide eating-related recommendations that improve the user's quality of life. To model the food-related characteristics of each person, it is essential to capture their food-related enjoyment using a Preferential Personal Food Model and their biological response to food using their Biological Personal Food Model. Inspired by the power of 3-dimensional color models for visual processing, we introduce a 6-dimensional taste-space for capturing culinary characteristics as well as personal preferences. We use event mining approaches to relate food with other life and biological events to build a predictive model that could also be used effectively in emerging food recommendation systems.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
