1. Research Center for Language Intelligence, Dalian University of Foreign Languages, Dalian 116044;
2. School of Software, Dalian University of Foreign Languages, Dalian 116044
Automatic citation intent classification is one of hot issues in the field of bibliometrics.The existing citation intention classification models engender the limitations in extracting textual features and fusing citation contextual features and citation external features. Therefore, a citation intent classification method based on MPNet pretraining and multi-head attention feature fusion is proposed. The position compensation structure is introduced to improve the masked language model and permuted Language model.The syntactic word-frequency features and structure features of citations are combined. A feature extraction method is proposed for citation intent classification task. The multi-head attention mechanism is introduced for feature fusion to improve the classification accuracy. The experimental results on ACL-ARC datasets demonstrate that the proposed method achieves better performance in citation intent classification task with robustness on the unbalanced data.
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2022, Vol. 35 
