Identifying schools from authors' texts using data mining

Document Type : Original Article

Authors

1 Faculty of Engineering Department of Computer, Shahrood Branch-Islamic Azad University

2 Shahrood University, Iran

Abstract

In the field of knowledge of philosophical schools, each person's thinking is different according to the type of attitude he can have regarding different schools. Recognizing the author's attitude and its similarity to each of the philosophical schools has always been one of the important issues in the field of humanities. In this article, a method based on deep learning is proposed to distinguish philosophical schools from text. In the proposed method, first the texts are normalized and redundant and meaningless words are removed. After the normalization stage, the text is broken into sentences and words, and then using the fasttext library, each word is converted into a numerical vector, after that, the features of the texts are extracted using the designed network, and finally, the system has learned and is ready to extract data, and by giving a new sentence, its similarity to each school is expressed. Based on the evaluation, the accuracy of the proposed method is 94%.

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References

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Applied and basic Machine intelligence research
Volume 1, Issue 2
December 2023
Pages 118-130

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