期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2017
卷号：8
期号：1
页码：9-13
语种：English
出版社：Ayushmaan Technologies
摘要：As human-beings, we daily need optimal energy, but most of the people are careless about food calories and nutrition’s suitability required for their health. Some people use some online web portals to calculate nutrition values, but with lacking of information that how to get nutrition naturally from food is the main objective for this research. People have personal preference for certain kind of food and to use their explicit data to get food recommendation according to their choices can be the solution. Therefore, explicit information has surety for accurate data and will be helpful to develop a framework that provides food recommendation. Furthermore, transforming the implied knowledge about nutrition into structured data is challenging, so Canadian Nutrient File database can be used to overcome this problem. We present a semantic framework using hybrid approach for combining “SELFNutritionData” web portal system and recommender system that uses the explicit information based on the users’ preference. The empirical evaluation of the proposed framework shows promising results for recommending the relevant food information with a superior users’ satisfaction.
关键词：Explicit Information;Food and Nutrition;Recommendation System;Hybrid Approach
