Deeplearning Model Used in Text Classification
Jingjing Cai, Jianping Li, Wei Li, Ji Wang
University of Electronic Science and Technology of China Shanghai Maritime University
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摘要与影响
Text classification is one of the most widely used natural language processing technologies. Common text classification applications include spam identification, news text classification, information retrieval, emotion analysis, and intention judgment, etc. Traditional text classifiers based on machine learning methods have defects such as data sparsity, dimension explosion and poor generalization ability, while classifiers based on deep learning network greatly improve these defects, avoid cumbersome feature extraction process, and have strong learning ability and higher prediction accuracy. For example, convolutional neural network (CNN)[I]. This paper introduces the process of text classification and focuses on the deep learning model used in text classification.
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学科主题
计算机 / AITopic Modeling
Text and Document Classification Technologies · Sentiment Analysis and Opinion Mining
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