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Deep Learning Based Text Classification: A Comprehensive Review

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arxiv 2004.03705 v3 pith:HEDVNXJ7 submitted 2020-04-06 cs.CL cs.LGstat.ML

Shervin Minaee , Nal Kalchbrenner , Erik Cambria , Narjes Nikzad , Meysam Chenaghlu , Jianfeng Gao This is my paper · ORCID
classification cs.CLcs.LGstat.ML
keywords learningclassificationdeeptextmodelsanalysiscomprehensivediscuss
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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 paper, we provide a comprehensive review of more than 150 deep learning based models for text classification developed in recent years, and 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 discuss future research directions.

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