| Issue |
EPJ Web Conf.
Volume 341, 2025
2nd International Conference on Advent Trends in Computational Intelligence and Communication Technologies (ICATCICT 2025)
|
|
|---|---|---|
| Article Number | 01003 | |
| Number of page(s) | 9 | |
| DOI | https://doi.org/10.1051/epjconf/202534101003 | |
| Published online | 20 November 2025 | |
https://doi.org/10.1051/epjconf/202534101003
A Heuristic Approach towards Book Genre Detection & Classification using Data Mining Technique
1 Professor, PG Department of Computer Science & Engineering, Sant Gadge Baba Amravati University, Amravati, Maharashtra, India
2 Research Scholar, PG Department of Computer Science & Engineering, Sant Gadge Baba Amravati University, Amravati, Maharashtra, India
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Published online: 20 November 2025
Abstract
Exploring the contextual knowledge in books has been crucial aspect of learning from year and years for the learners. Present Library management systems provide quick access towards the availability of the books as well as provides the entire record of its usage. But having said that it also experiences some challenges like predicting the class/ Genre of the book and recommending that book for a corresponding user. This automated utility about books assessment will play a very pivotal role for its users. In this paper data mining techniques (ensembled learning models) are used which are capable enough to predict the genre of a book from the set of various book titles (Sample size of 5700 books taken here) and it will recommend the competent user to explore the book. This approach will open new verticals for the researchers to allow learners to choose the books at their will & area of interest they want to explore.
Key words: Library Management System / Genre Detection / Ensembled Learning / Data mining / recommendation system
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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