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Tree-Based Convolutional Neural NetworksBackground and Related Work

Tree-Based Convolutional Neural Networks: Background and Related Work [In this chapter, we introduce the background of neural networks and review related literature. Section 2.1 introduces the general neural network and its learning algorithm—backpropagation. Section 2.2 addresses specialty of natural language processing, and introduces neural language models and word embedding learning. Section 2.3 introduces existing structure-sensitive neural networks, including the convolutional neural network, recurrent neural network, and recursive neural network.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Tree-Based Convolutional Neural NetworksBackground and Related Work

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/lp/springer-journals/tree-based-convolutional-neural-networks-background-and-related-work-efUJn90JgK
Publisher
Springer Singapore
Copyright
© The Author(s) 2018
ISBN
978-981-13-1869-6
Pages
9 –35
DOI
10.1007/978-981-13-1870-2_2
Publisher site
See Chapter on Publisher Site

Abstract

[In this chapter, we introduce the background of neural networks and review related literature. Section 2.1 introduces the general neural network and its learning algorithm—backpropagation. Section 2.2 addresses specialty of natural language processing, and introduces neural language models and word embedding learning. Section 2.3 introduces existing structure-sensitive neural networks, including the convolutional neural network, recurrent neural network, and recursive neural network.]

Published: Oct 2, 2018

Keywords: Neural network; Neural language modeling; Word embeddings; Convolutional neural network; Recurrent neural network; Recursive neural network

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