Open Access
ARTICLE
Personalized Nutrition Recommendation for Diabetic Patients Using Optimization Techniques
Bhavithra Janakiraman1,*, Saradha Arumugam2
1 Department of Computer Science and Engineering, Dr. Mahalingam College of Engineering and Technology, Pollachi, Tamilnadu 642003, India
2 Department of Computer Science and Engineering, Institute of Road and Transport Technology, Erode, Tamilnadu 638316, India
* Corresponding Author: Bhavithra Janakiraman,
Intelligent Automation & Soft Computing 2020, 26(2), 269-280. https://doi.org/10.31209/2019.100000150
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.
Keywords
Cite This Article
B. Janakiraman and S. Arumugam, "Personalized nutrition recommendation for diabetic patients using optimization techniques,"
Intelligent Automation & Soft Computing, vol. 26, no.2, pp. 269–280, 2020. https://doi.org/10.31209/2019.100000150