[2004.03705] Deep Learning Based Text Classification: A Comprehensive Reviewopen searchopen navigation menucontact arXivsubscribe to arXiv mailings

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 work, we provide a detailed 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.

10 mentions: @omarsar0@dennybritz@WilliamWangNLP@BDWissel@jordi_delatorre
Keywords: deep learning
Date: 2020/06/27 20:21

Referring Tweets

@omarsar0 If you are getting started with deep learning-based NLP most people recommend you start by learning to write code for classification tasks. I say that's great but you also need to build intuition on the tasks you are writing code for. This may help: t.co/QgSnrT5j8E t.co/lV0ixoHC2k
@BDWissel Excellent review of #DeepLearning methods for text classification. How can these be used to improve medicine? It is only a matter of time. t.co/CLjJ6sxjBK

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