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Hybrid Book Recommendation System Integrate with Association Rule Mining

International Journal of Business Analytics and Intelligence

Volume 11 Issue 2

Published: 2023
Author(s) Name: Sushma Malik, Anamika Rana, Mamta Bansal | Author(s) Affiliation: School of Engg. & Tech., Dept. of CSE, Shobhit Inst. of Engg. & Tech., Meerut, Uttar Pradesh, India.
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Abstract

The best knowledge management systems are recommender systems, which let consumers filter out irrelevant data and provide tailored recommendations based on their past historical data and related products they are looking for online. A recommender system provides suggestions to customers in various circumstances. Online book sellers today engage in a number of competitive activities. One of the more powerful techniques for increasing earnings and keeping customers is the recommendation system. Books that will attract buyers must be recommended by the book recommendation system. This study proposes a system for recommending books that combines association rule mining, collaborative filtering and content filtering.

Keywords: Book Recommender System (BRS), Collaborative Filtering (CF), Content Based Filtering (CB), Association Rule (AR), E-Commerce Sites

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