A Short Text Classification Method Based on <i>N</i> ‐Gram and CNN

Chinese Journal of ElectronicsVolume 29, Issue 2 p. 248-254 ArticleFree Access A Short Text Classification Method Based on N-Gram and CNN Haitao Wang, Haitao Wang College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, 454000 ChinaSearch for more papers by this authorJie He, Corresponding Author Jie He 1760778431@qq.com College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, 454000 ChinaSearch for more papers by this authorXiaohong Zhang, Xiaohong Zhang College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, 454000 ChinaSearch for more papers by this authorShufen Liu, Shufen Liu College of Computer Science and Technology, Jilin University, Changchun, 130012 ChinaSearch for more papers by this author Haitao Wang, Haitao Wang College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, 454000 ChinaSearch for more papers by this authorJie He, Corresponding Author Jie He 1760778431@qq.com College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, 454000 ChinaSearch for more papers by this authorXiaohong Zhang, Xiaohong Zhang College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, 454000 ChinaSearch for more papers by this authorShufen Liu, Shufen Liu College of Computer Science and Technology, Jilin University, Changchun, 130012 ChinaSearch for more papers by this author First published: 01 March 2020 https://doi.org/10.1049/cje.2020.01.001Citations: 8AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Abstract Text classification is a fundamental task in Nature language process (NLP) application. Most existing research work relied on either explicate or implicit text representation to settle this kind of problems, while these techniques work well for sentence and can not simply apply to short text because of its shortness and sparseness feature. Given these facts that obtaining the simple word vector feature and ignoring the important feature by utilizing the traditional multi-size filter Convolution neural network (CNN) during the course of text classification task, we offer a kind of short text classification model by CNN, which can obtain the abundant text feature by adopting none linear sliding method and N-gram language model, and picks out the key features by using the concentration mechanism, in addition employing the pooling operation can preserve the text features at the most certain as far as possible. The experiment shows that this method we offered, comparing the traditional machine learning algorithm and convolutional neural network, can markedly improve the classification result during the short text classification. Citing Literature Volume29, Issue2March 2020Pages 248-254 RelatedInformation