基于深度学习的文本分析综述

Liu Ying, Li Huidi
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引用次数: 3

摘要

利用数据挖掘技术进行文本分析,可以获取和发现隐含知识,这是一个从文本信息描述、特征提取到知识形成的过程。文本数据和语义信息的空间表示可以使用端到端深度学习算法进行简化和识别。本文综述了基于深度学习的文本分析。本文首先分析了文本学习的过程,然后总结了文本分析学习模型,包括卷积神经网络、递归神经网络和深度学习算法融合等。进一步介绍了基于深度学习的文本分析的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Review of Text analysis Based on Deep Learning
Text analysis using data mining technology can acquire and discover implicit knowledge, which is a process from text information description and feature extraction to knowledge formation. The spatial representation of text data and semantic information can be simplified and identified using end-to-end deep learning algorithms. This paper reviews the text analysis based on deep learning. Firstly, this article analyzes the process of the text learning, then text analysis learning models are summarized, including convolutional neural networks, recurrent neural networks, and deep learning algorithm fusion and so on. Furthermore, the applications of text analysis based on deep learning are introduced.
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