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Deep Learning-based Text Classification: A Comprehensive Review
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DOI：10.1145/3439726.png)
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Abstract
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Deep learning-based models have surpassed classical machine learning-based approaches in various text classification tasks, including sentiment analysis, news categorization, question answering, and natural language inference. In this article, we provide a comprehensive review of more than 150 deep learning-based models for text classification developed in recent years, and we discuss their technical contributions, similarities, and strengths. We also provide a summary of more than 40 popular datasets widely used for text classification. Finally, we provide a quantitative analysis of the performance of different deep learning models on popular benchmarks, and we discuss future research directions.
Keywords:
Text classification
sentiment analysis
question answering
news categorization
deep learning
natural language inference
topic classification
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