Book Genre Classification Based on Reviews of Portuguese-Language Literature

被引:2
|
作者
Scofield, Clarisse [1 ]
Silva, Mariana O. [1 ]
de Melo-Gomes, Luiza [1 ]
Moro, Mirella M. [1 ]
机构
[1] Univ Fed Minas Gerais, Belo Horizonte, MG, Brazil
关键词
Text classification; Book genre classification; Online reviews; Multiclass classification;
D O I
10.1007/978-3-030-98305-5_18
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Automatic 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.
引用
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页码:188 / 197
页数:10
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