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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM35001

Book Recommendation System with Integrated Chatbot

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM35001

Volume:

8 |

5 |

May 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM35001

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

VP

Vedant Pawar

MD

Mahesh Dunde

GL

Gaurav Lavekar

PAD

Prof. Anand Dhawale

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Abstract

In today’s digital era, the overwhelming volume of available literature necessitates a more personalized approach to book recommendations. Our research aims to address this need by pioneering a solution that integrates hybrid filtering methodologies and advanced chatbot technology driven by machine learning algorithms. By leveraging these cutting-edge techniques, we aspire to redefine the book discovery experience, providing tailored recommendations that resonate with individual preferences. Through the fusion of popularized, collaborative and content-based alongside the capabilities of machine learning models for natural language processing, our system not only enhances recommendation accuracy but also fosters real-time interaction, ultimately enhancing user satisfaction and engagement in the realm of literature.

KEYWORDS

Personalized book recommendations Hybrid filtering methodologies chatbot technology machine learning algorithms Collaborative filtering Content-based filtering Natural language processing Recommendation accuracy.

Cite This Article

Vedant Pawar, Mahesh Dunde, Gaurav Lavekar, Prof. Anand Dhawale, "Book Recommendation System with Integrated Chatbot," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 5, May 2024. https://doi.org/10.55041/IJSREM35001

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12/31/45440

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Double-Blind Peer Review

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