Food Recommender System

Abstract

With the increased interest in living a healthy lifestyle, research into applications that assist people to improve their lifestyles have also increased. This is particularly true with the development of systems and middleware which provide services utilizing various types of data. Typically, people who want to change lifestyle choices for better health and fitness, focus on their diets. As such, further research into applications that can inform consumers about appropriate food choices and that takes into account individual preferences is required. People make decisions every day with the range varying from choice of films, places to visit, apparels, consumer goods, etc. There are too many choices and a little time to explore them all. Recommendation systems help people make decisions in these complex information spaces. Simply they compare user interest acquired from his/her profile with some reference characteristics and predict the rating that the user would give. Recommender systems have become extremely common in recent years, and are applied in a variety of applications