A Survey on Text Classification: From Traditional to Deep Learning

Text classification is the most fundamental and essential task in natural language processing. The last decade has seen a surge of research in this area due to the unprecedented success of deep learning. Numerous methods, datasets, and evaluation metrics have been proposed in the literature, raising the need for a comprehensive and updated survey. This paper fills the gap by reviewing the state-of-the-art approaches from 1961 to 2021, focusing on models from traditional models to deep learning. We create a taxonomy for text classification according to the text involved and the models used for feature extraction and classification. We then discuss each of these categories in detail, dealing with both the…

• NN
  National Natural Science Foundation of China

  Award: U20B2053 and 61872022
• SK
  State Key Laboratory of Software Development Environment

  Award: SKLSDE-2020ZX-12
• NK
  National Key Research and Development Program of China

  Award: 2021YFB1714800