Hybrid Recommendation System for e-Pharmacy
Aniket Karanje, Anurag Babar, Jay Pawar, Pratik Kshirsagar, Prof. Mayuri Agrawal · International Journal of Advanced Research in Science Communication and Technology · 2024
In the ever-evolving field of recommendation systems, the importance of providing users with precise and personalized suggestions cannot be understated. This paper delves into the realm of medicine recommendation and explores the use of hybrid recommendation algorithms, combining content-based and collaborative filtering techniques. The study prioritizes content-based recommendation using cosine similarity and Singular Value Decomposition (SVD) while emphasizing their effectiveness in recommending medicines with similar formulae. The proposed hybrid approach leverages a rich dataset from Kaggle and integrates user-friendly features, linking to popular online pharmaceutical platforms. By analyzing the architecture and design, this paper demonstrates the superiority of hybrid filtering in the context of medicine recommendation