適地性個人化健康管理食譜推薦系統

• Main Authors: Min-Ci Sun, 孫旻祺
• Other Authors: Guan-Ling Lee
• Format: Others
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/28120575820415138506

碩士 === 國立東華大學 === 資訊工程學系 === 103 === We are living in the age of the Internet, an age denoted by vast quantities of information that are simply impossible to make sense of with our human minds. With so many facts and opinions on the web today, how do we differentiate between types of information and figure out exactly what we need? Take the simple example of finding a recipe. There are perhaps hundreds of different recipes that all make the same dish, but how does one go about deciding which recipe is the right one? Excessive network resources available today can easily overwhelm the average user, so our end objective is to design a system that can filter out irrelevant information and provide accurate and useful recommendations in order to give users the information they want, in particular information about cooking recipes. The economy has reached a state of prosperity and stability such that the struggle of putting food on the table is no longer the concern of the average citizen. A lot of people today have the financial means of sustaining a diet that is both healthy and appetizing, but figuring out that diet can be a troublesome task; what might be healthy or tasty to one person might not be suitable for another. If there was one absolute way to eat, why are there so many different named diets out there? People have different health issues and tastes, so our system aims to resolve that problem by providing each user with a unique and personalized recommendation. The content-based recommendation system we developed was implemented to support mobile device functionality, using Google’s Android operating system and the Java programming language. Its main function involves giving a survey to the user, and then based on the user’s response to the questions (questions like “do you usually eat what you want to eat or do you only eat based on what is in your refrigerator?”), it presents the user with a list of corresponding recipes that fit the user’s personal habits and requirements. To make life even easier, it also utilizes location-based services to get ahold of information about the user’s general region, as different places likely offer different ingredients. Through these features, our system can effectively improve users’ diets without sacrificing convenience and comfort.