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Book Recommendation System Using Item-based Collaborative Filtering Technique and Cosine Similarity

Richa Patel, Pradnya Chaudhari, Pooja Patil, Jyostna Sonawane, Dhanashri Patil

Abstract


The quality of generated recommendations in collaborative filtering recommendation algorithms is determined by how accurately the similarity is calculated. There are multiple ways to improve the accuracy of similarity calculation. All the methods include calculation of user-ratings matrix, user-attribute matrix and item-attribute matrix. Collaborative filtering has two approaches namely user-based Collaborative Filtering and item-based collaborative filtering. This paper discusses item-based collaborative filtering using cosine similarity for determining similar items.


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References


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