Bhavithra Janakiraman1,*, Saradha Arumugam2
Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 269-280, 2020, DOI: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. More >
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