What Does a TextCNN Learn?

TextCNN, the convolutional neural network for text, is a useful deep learning algorithm for sentence classification tasks such as sentiment analysis and question classification. However, neural networks have long been known as black boxes because interpreting them is a challenging task. Researchers...

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Bibliographic Details
Main Authors Gong, Linyuan, Ji, Ruyi
Format Journal Article
LanguageEnglish
Published 18.01.2018
Subjects
Computer Science - Computation and Language
Computer Science - Learning
Statistics - Machine Learning
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Summary:TextCNN, the convolutional neural network for text, is a useful deep learning algorithm for sentence classification tasks such as sentiment analysis and question classification. However, neural networks have long been known as black boxes because interpreting them is a challenging task. Researchers have developed several tools to understand a CNN for image classification by deep visualization, but research about deep TextCNNs is still insufficient. In this paper, we are trying to understand what a TextCNN learns on two classical NLP datasets. Our work focuses on functions of different convolutional kernels and correlations between convolutional kernels.
DOI:10.48550/arxiv.1801.06287