Au sujet de ce document
- sl:arxiv_author :
- sl:arxiv_firstAuthor : Shervin Minaee
- sl:arxiv_num : 2004.03705
- sl:arxiv_published : 2020-04-06T02:00:30Z
- sl:arxiv_summary : 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.@en
- sl:arxiv_title : Deep Learning Based Text Classification: A Comprehensive Review@en
- sl:arxiv_updated : 2020-04-06T02:00:30Z
- sl:bookmarkOf : https://arxiv.org/abs/2004.03705
- sl:creationDate : 2020-10-11
- sl:creationTime : 2020-10-11T01:16:13Z
Documents with similar tags (experimental)
Préférences...