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4Book Genre Prediction Using NLP: A Review

Kuldeep Vayadande^1*, Preeti Bailke¹, Ashutosh M. Kulkarni¹, R. Kumar² and Ajit B. Patil³

¹Vishwakarma Institute of Technology, Pune, Maharashtra, India

²VIT-AP University, Inavolu, Beside AP Secretariat, Amaravati AP, India

³KIT's College of Engineering, Kolhapur, Maharashtra, India

Abstract

Book genre prediction is a crucial task in the field of literature, and the use of NLP techniques has significantly improved the accuracy of genre prediction systems. This survey paper provides an overview of recent research on book genre prediction using NLP techniques such as lexical analysis and neural networks. The paper discusses various approaches, datasets, and evaluation metrics used in the literature and presents a comparative analysis of the different techniques based on their effectiveness in genre prediction. The survey highlights the potential impact of NLP techniques on the field of literature, emphasizing the importance of accurate genre prediction for various applications such as recommendation systems and book marketing. However, there are still challenges to be addressed, such as the lack of standard evaluation metrics and the need to better understanding the relationship between language features and genre classification. The survey concludes with a discussion on the future research directions in this field, such as the use of deep learning techniques and the development of more diverse and representative datasets.

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