Yuhao Zhao

Work place: Software College, Shenyang Normal University, Shenyang 110034, China

E-mail: yslinhit@163.com


Research Interests: Image Processing, Natural Language Processing


Yuhao Zhao graduted with a Bachelor of Engineering from Changzhi University in 2015. In his college, after completing the learning task, he interests in exploring his professional knowledge. Now, he is a undergraduate of Master of Engineering. His research interests include nature language processing and image processing.

Author Articles
A Multi-channel Character Relationship Classification Model Based on Attention Mechanism

By Yuhao Zhao Hang Li Shoulin Yin

DOI: https://doi.org/10.5815/ijmsc.2022.01.03, Pub. Date: 8 Feb. 2022

Relation classification is an important semantic processing task in the field of natural language processing. The deep learning technology, which combines Convolutional Neural Network and Recurrent Neural Network with attention mechanism, has always been the mainstream and state-of-art method. The LSTM model based on recurrent neural network dynamically controls the weight by gating, which can better extract the context state information in time series and effectively solve the long-standing problem of recurrent neural network. The pre-trained model BERT has also achieved excellent results in many natural language processing tasks. This paper proposes a multi-channel character relationship classification model of BERT and LSTM based on attention mechanism. Through the attention mechanism, the semantic information of the two models is fused to get the final classification result. Using this model to process the text, we can extract and classify the relationship between the characters, and finally get the relationship between the characters included in this paper. Experimental results show that the proposed method performs better than the previous deep learning model on the SemEval-2010 task 8 dataset and the COAE-2016-Task3 dataset. 

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