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作者:

Luan, Yuandong (Luan, Yuandong.) | Lin, Shaofu (Lin, Shaofu.)

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摘要:

With the rapid development of deep learning technology, CNN and LSTM have become two of the most popular neural networks. This paper combines CNN and LSTM or its variant and makes a slight change. It proposes a text classification model named NA-CNN-LSTM or NA-CNN-COIF-LSTM, which has no activation function in CNN. The experimental results on the subjective and objective text categorization dataset [1] show that the proposed model has better performance than the standard CNN or LSTM. © 2019 IEEE.

关键词:

Classification (of information) Deep learning Long short-term memory Text processing

作者机构:

  • [ 1 ] [Luan, Yuandong]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 2 ] [Lin, Shaofu]Faculty of Information Technology, Beijing University of Technology, Beijing, China

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来源 :

年份: 2019

页码: 352-355

语种: 英文

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次: 128

ESI高被引论文在榜: 0 展开所有

万方被引频次:

中文被引频次:

近30日浏览量: 7

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