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- W4360982204 abstract "In recent times, Recommendation System (RS) performs a main position in assisting clients to discover the best books of their interest. A novel solution for recommending accurate books to the user was proposed by applying an integration of the Collaborative Filtering (CF) and Content-Based Filtering (CBF) with Popularity Index (PI) methods. It recommends books to the registered users in the system and also to the new users. Firstly, the input data which is document level reviews transferred from analysis stage to analyzes the sentiment of the user and removes noisy data. Now, grouping of reviewers is done dependent on the kind of review they are given and their personal details such as age, region and sex by utilizing MySQL. CBF system and CF system are used to filter reviews. In additional, PI technique is also used to retrieve data from popular books by ranking in the database. Finally, after filtering, Recommender suggests the books to the users based on their interests accurately which satisfies the customer with an average accuracy of 85%." @default.
- W4360982204 created "2023-03-30" @default.
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- W4360982204 date "2023-01-01" @default.
- W4360982204 modified "2023-09-29" @default.
- W4360982204 title "Comparative Analysis of Book Recommendation System Based on User Reviews Using Hybrid Methods" @default.
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- W4360982204 doi "https://doi.org/10.1007/978-3-031-27622-4_1" @default.
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