Journal
2020 2ND INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE COMMUNICATION AND NETWORK SECURITY (CSCNS2020)
Volume 336, Issue -, Pages -Publisher
E D P SCIENCES
DOI: 10.1051/matecconf/202133606022
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Funding
- China Association of higher education [2020XXHYB13]
- Social science fund of Shaanxi Province [2019Q019]
- Scientific research project of higher education of Shaanxi Higher Education Association [XGH19056]
- Shaanxi higher Education teaching Reform Research Project [19BY130]
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The improvement of deep learning technology has accelerated the development of text classification, different word embedding methods and deep learning models can help automatically classify text and quickly summarize information from a large amount of data.
Traditional manual text classification method has been unable to cope with the current huge amount of data volume. The improvement of deep learning technology also accelerates the technology of text classification. Based on this background, we presented different word embedding methods such as word2vec, doc2vec, tfidf and embedding layer. After word embedding, we demonstrated 8 deep learning models to classify the news text automatically and compare the accuracy of all the models, the model '2 layer GRU model with pretrained word2vec embeddings' model got the highest accuracy. Automatic text classification can help people summary the text accurately and quickly from the mass of text information. No matter in the academic or in the industry area, it is a topic worth discussing.
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