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Book Recommendation System Using Collaborative Filtering

K. TULASI KRISHNA KUMAR, D. UPENDRA

Assistant Professor, Training & Placement Officer, MCA Final Semester,

Master of Computer Applications,

Sanketika Vidya Parishad Engineering College, Vishakhapatnam, Andhra Pradesh, India.

Abstract:
Due to the extreme expansion of digital book platforms, users are having trouble finding relevant books because of the enormous amount of information. Recommendation systems are beneficial against this complication as they offer recommendations based on what users are interested in. Good reads data is used to implement and analyze a collaborative filtering approach to item-based recommendation on a big data environment, resulting in an improved book recommendation system. This system utilizes user-based and item-based collaborative filtering and aims at refining the accuracy of the recommendations by implementing Singular Value Decomposition (SVD) and cosine similarity.

INDEX TERMS: : Recommendation System, Collaborative Filtering, Book Recommendation, SVD, Flask Web Application