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Text classification system of academic papers based on hybrid Bert-BiGRU model

机译:基于混合Bert-BiGRU模型的学术论文文本分类系统

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The text classification is an important research orientation in the fields of information retrieval and data mining, which has extensive applications in the practical work and scientific research and its research on the algorithm is always a hot topic. At present, the study on the long text like academic texts mainly focuses on abstract extraction. Whereas, due to the complicated content of the text format, there is very little classification research according to the text structure. In this study, the academic texts are classified based on Bidirectional Encoder Representations from Transformers and Bidirectional Gated Recurrent Unit (BERT-BiGRU) model.
机译:文本分类是信息检索和数据挖掘领域的重要研究方向,在实践和科学研究中有着广泛的应用,其对算法的研究一直是一个热门话题。目前,对像学术文本这样的长文本的研究主要集中在摘要提取上。然而,由于文本格式的内容复杂,因此根据文本结构进行分类的研究很少。在这项研究中,学术文献是基于来自变压器的双向编码器表示形式和双向门控递归单元(BERT-BiGRU)模型进行分类的。

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