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What is Deep Neural Network

Neural Networks for Natural Language Processing
Neural Network with more than two layers in depth is known as deep neural network.
Published in Chapter:
Deep Learning Approach for Extracting Catch Phrases from Legal Documents
Kayalvizhi S. (SSN College of Engineering, India) and Thenmozhi D. (SSN College of Engineering, India)
Copyright: © 2020 |Pages: 16
DOI: 10.4018/978-1-7998-1159-6.ch009
Abstract
Catch phrases are the important phrases that precisely explain the document. They represent the context of the whole document. They can also be used to retrieve relevant prior cases by the judges and lawyers for assuring justice in the domain of law. Currently, catch phrases are extracted using statistical methods, machine learning techniques, and deep learning techniques. The authors propose a sequence to sequence (Seq2Seq) deep neural network to extract catch phrases from legal documents. They have employed several layers, namely embedding layer, encoder-decoder layer, projection layer, and loss layer to build the deep neural network. The methodology is evaluated on IRLeD@FIRE-2017 dataset and the method has obtained 0.787 and 0.607 as mean average precision and recall scores respectively. Results show that the proposed method outperforms the existing systems.
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The Threat of Intelligent Attackers Using Deep Learning: The Backoff Attack Case
Graph structure which provides as output a nonlinear combination of its inputs. It has been proven to be a universal function approximator.
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