2023 |
Volume 11 |
Issue 2
Hybrid Book Recommendation System Integrate with Association Rule Mining
1.
Sushma Malik
– School Of Engg. & Tech., Dept. Of Cse, Shobhit Inst. Of Engg. & Tech., Meerut, Uttar Pradesh, India.
2.
Anamika Rana
– School Of Engg. & Tech., Dept. Of Cse, Shobhit Inst. Of Engg. & Tech., Meerut, Uttar Pradesh, India.
3.
Mamta Bansal
– School Of Engg. & Tech., Dept. Of Cse, Shobhit Inst. Of Engg. & Tech., Meerut, Uttar Pradesh, India.
Received
12-Feb-2024
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Accepted
-
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Published
12-Feb-2024
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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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