Author(s)

Bin Yang, Dakui Li, Nanhai Yang

Corresponding Author

Dakui Li

ABSTRACT

The multi-label text classifications of accusations and relevant law articles are important tasks in the construction of intelligent justice. In this paper, we apply multi-level attention mechanisms to the multi-core CNN, and combine the BERT sentence embedding to propose the BERT-ACNN for the tasks. The architecture can selectively extract features and incorporate features extracted by the BERT pre-training language model. Experiments show that our model can achieve better results on the CAIL2018-Small dataset than Average Pooling models, RNNs and CNN. Finally, we improve the performance of BERT-ACNN by oversampling and increasing the number of convolution layers.

KEYWORDS

Multi-label text classifications,Intelligent Justice, BERT Sentence Embedding, Attention, CNN