Yoori Oh, Jieun Choi, Yoonhee Kim

KIPS Transactions on Software and Data Engineering, Vol. 5, No. 6, pp. 289-294, Jun. 2016
10.3745/KTSDE.2016.5.6.289,   PDF Download:
Keywords: Dietary Coaching Method, Personalized, Clustering Analysis
Abstract

In recent times, as most people develop keen interest in health management, the importance of cultivating dietary habits to prevent various chronic diseases is emphasized. Subsequently, dietary management systems using a variety of mobile and web application interfaces have emerged. However, these systems are difficult to apply in real world and also do not provide personalized information reflective of the user's situation. Hence it is necessary to develop a personalized dietary management and recommendation method that considers user's body state information, food analysis and other essential statistics. In this paper, we analyze nutrition using self-organizing map (SOM) and prepare data about nutrition using clustering. We provide a substitute food recommendation method and also give feedback about the food that user wants to eat based on personalized criteria. The experiment results show that the distance between input food and recommended food of the proposed method is short compared to the recommended food results using general methods and proved that nutritional similar food is recommended.

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