Research on Automatic Classification Based on Academic Text Corpus

Chuan Jiang, Zhixiao Zhao, Na Wu, Litao Lin

Article ID: 3649
Vol 6, Issue 5, 2023

VIEWS - 1414 (Abstract)

Abstract


Recognizing the discipline category of the abstract text is of great significance for automatic text recommendation and knowledge mining. Therefore, this study obtained the abstract text of social science and natural science in the Web of Science 2010-2020, and used the machine learning model SVM and deep learning model TextCNN and SCI-BERT models constructed a discipline classification model. It was found that the SCI-BERT model had the best performance. The precision, recall, and F1 were 86.54%, 86.89%, and 86.71%, respectively, and the F1 is 6.61% and 4.05% higher than SVM and TextCNN. The construction of this model can effectively identify the discipline categories of abstracts, and provide effective support for automatic indexing of subjects.


Keywords


Deep Learning; SCI-BERT; Academic Literature; Automatic Indexing

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References


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DOI: https://doi.org/10.24294/ijmss.v6i5.3649

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