Classification of Chinese Hotel Reviews Based on GCN. Issue 1 (January 2021)

• Record Type: Journal Article
• Authors: Lin, Zhiyu; Zhang, Jingxuan; Zhang, Haoxi
• Is Part Of: Journal of physics. Volume 1757:Issue 1(2021)
• Publication Date: 2021-01
• Subjects: Text Classification -- Non - Euclidean Space Data -- Graph Convolution Neural Network -- Word Vector; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1757/1/012053
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Text classification is a fundamental part of natural language processing and can help with many downstream tasks, such as emotion analysis, question and answer systems, and recommendation systems. The graph convolution neural network has the natural superiority in the non - Euclidean space data. For Chinese text data, there is a lot of correlation between the data, using the graph convolutional neural network for text classification can achieve good results. In our experiment, we use a simple one-hot encoding of the word vector to process our words and use of the graph convolutional neural network can achieve 94.24% accuracy in our data set.