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A Survey on Deep Learning-Based Automatic Text Summarization Models - 2021

A Survey On Deep Learning-Based Automatic Text Summarization Models

Survey Paper on Deep Learning-Based Automatic Text Summarization Models

Research Area:  Machine Learning

Abstract:

Text summarization is referred to the process of rewriting a particular content into its brief version by understanding it. It is a serious need to obtain concise and relevant information from huge information. Automatic text summarization is fast-growing research area in natural language processing from last few years. It has improved from simple heuristics to neural network-based text summarization techniques. The extractive and abstractive text summarization generate the condensed text which saves time in reading the entire document. The abstractive approach is more complex as it needs natural language processing and neural network. Due to the availability of huge unsupervised data, traditional approach fails to provide accuracy in text summarization. The deep learning-based text summarization model gives a good performance as compared to the conventional techniques. In this paper, we have reviewed the recent work on text summarization based on deep learning techniques.

Keywords:  
Deep Learning
Automatic Text Summarization
Machine Learning

Author(s) Name:  P. G. Magdum & Sheetal Rathi

Journal name:  

Conferrence name:  Advances in Artificial Intelligence and Data Engineering

Publisher name:  Springer

DOI:  10.1007/978-981-15-3514-7_30

Volume Information:  pp 377–392