• ADARSHA S V
• ARJUN GARG
• ADITYA
• ADARSH SANGAM
• PRAGATHI M

Book recommendation systems are designed to suggest books to readers based on their interests and reading history. However, these systems can be influenced by hidden biases, which can lead to the exclusion of certain authors or literature and perpetuate harmful stereotypes. These systems use algorithms to analyze users' reading histories and make recommendations based on the books that they have previously read. However, these systems are not perfect, and they can be biased in various ways. This research paper will examine the presence of hidden bias in book recommendation systems and its impact on readers. It will explore the ways in which these biases can be introduced, including through the data used to train the recommendation algorithms and the personal biases of those who design and implement the systems.

Book recommendation, Hidden bias, Recommendation algorithms.

"HIDDEN BIAS IN BOOK RECOMMENDATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.b583-b590, May-2023, Available :http://www.jetir.org/papers/JETIR2305176.pdf

"HIDDEN BIAS IN BOOK RECOMMENDATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppb583-b590, May-2023, Available at : http://www.jetir.org/papers/JETIR2305176.pdf