@Article{2019.100000150,
AUTHOR = {Bhavithra Janakiraman, Saradha Arumugam},
TITLE = {Personalized Nutrition Recommendation for Diabetic Patients Using  Optimization Techniques},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {26},
YEAR = {2020},
NUMBER = {2},
PAGES = {269--280},
URL = {http://www.techscience.com/iasc/v26n2/39944},
ISSN = {2326-005X},
ABSTRACT = {Personalization in recommendation system has been emerging as the most 
predominant area in service computing. Collaborative filtering and content 
based approaches are two major techniques applied for recommendation. 
However, to improve the accuracy and enhance user satisfaction, optimization 
techniques such as Ant Colony and Particle Swarm Optimization were analyzed 
in this paper. For theoretical analysis, this paper investigates web page 
recommender system. For experimentation, Diabetic patient’s health records 
were investigated and recommendation algorithms are applied to suggest 
appropriate nutrition for improving their health. Experiment result shows that 
Particle Swarm Optimization outperforms other traditional methods with 
improved performance and accuracy.},
DOI = {10.31209/2019.100000150}
}