Journal of East China Normal University(Natural Science) ›› 2022, Vol. 2022 ›› Issue (2): 67-75.doi: 10.3969/j.issn.1000-5641.2022.02.008

• Computer Science • Previous Articles     Next Articles

Bi-directional long short-term memory and bi-directional gated attention networks for text classification

Genmei TONG1, Min ZHU2,*()   

  1. 1. School of Computer Science and Technology, East China Normal University, Shanghai 200062, China
    2. School of Data Science and Engineering, East China Normal University, Shanghai 200062, China
  • Received:2020-11-09 Online:2022-03-25 Published:2022-03-28
  • Contact: Min ZHU


In this paper, we propose the construction of a bi-directional fully connected structure for better extraction of context information. We also propose the construction of a bi-directional attention structure for compressing matrices containing rich text features into a vector. The bi-directional fully connected structure and the gated structure are then combined. This research demonstrates that the proposed combined structure has a net positive effect on text classification accuracy. Finally, by combining these three structures and a bi-direction long short-term memory, we propose a new text classification model. Using this model, we obtained competitive results on seven commonly used text classification datasets and achieved state-of-the-art results on five of them. Experiments showed that the combination of these structures can significantly reduce classification errors.

Key words: text classification, attention, long short-term memory

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