Authors :
Priyanka S Talekar, Dr. Raghavendra G S, Basavaraj Vaddatti.
Volume/Issue :
Volume 4 - 2019, Issue 5 - May
Google Scholar :
https://goo.gl/DF9R4u
Scribd :
https://bit.ly/2ZhV1Oo
Abstract :
The purchasing behavior of the user is influenced by the recommendations provided to the products. Recommendation can be in the form of review or rating given to a particular product. The food consumed by the peoples includes carbohydrates, fat, protein, minerals and vitamins and any lack of nutrition leads to serious health issues. In this paper, we propose a recommendation system that is trained from the reviews provided by the buyer who has previously used the same product. NutriSmart application recommends the product to buyer based on the experience of the user who has used the same product. Every individual have their own food habits and based on likes and dislikes of user, suggesting an optimized nutrition becomes essential to maintain progress and health of the user. The proposed recommendation system uses deep learning algorithm and genetic algorithm to provide the best possible recommendation.
Keywords :
Recommendation System, Optimized Nutrition, Genetic Algorithm.
The purchasing behavior of the user is influenced by the recommendations provided to the products. Recommendation can be in the form of review or rating given to a particular product. The food consumed by the peoples includes carbohydrates, fat, protein, minerals and vitamins and any lack of nutrition leads to serious health issues. In this paper, we propose a recommendation system that is trained from the reviews provided by the buyer who has previously used the same product. NutriSmart application recommends the product to buyer based on the experience of the user who has used the same product. Every individual have their own food habits and based on likes and dislikes of user, suggesting an optimized nutrition becomes essential to maintain progress and health of the user. The proposed recommendation system uses deep learning algorithm and genetic algorithm to provide the best possible recommendation.
Keywords :
Recommendation System, Optimized Nutrition, Genetic Algorithm.
