Abstract
AbstractAutomatic book genre classification is a hard task as it requires the whole book’s content or a high-quality summary, which is challenging to write automatically. On the other hand, online reviews are an accessible resource for readers to evaluate a book or even get a general sense about it, including its genre. As the amount of book reviews is always increasing, using such information to genre classification needs a robust solution to deal with high volumes of data. In such a context, we introduce a model for automatically classifying book genres by analyzing online text reviews. We build a dataset of compiled texts from online book reviews. Then, we use multiple machine learning algorithms to categorize a book into a specific genre. Such a process enables to compare algorithms and detect the best classifiers. Hence, the most efficient machine learning algorithm completed the task with an accuracy of 96%; i.e., the proposed model is convenient for various information retrieval systems due to its high certainty and efficiency.KeywordsText classificationBook genre classificationOnline reviewsMulticlass classification
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