A Study of Implementation of Deep Learning Techniques for Text Summarization

Authors

  • Bilkeesa Akhter M.Tech Scholar, Department of Electronics and Communication Engineering, RIMT University Mandi Gobingrah, Punjab India Author
  • Monika Mehra Professor, Department of Electronics and Communication Engineering, RIMT University Mandi Gobingrah Punjab India Author

Keywords:

Summarize text, Deep Learning Techniques, Effective, Automatization

Abstract

To automatically summarize a piece of  material, the length of the original text must be reduced  while the content's important informative parts and  significance are preserved. As a result, automating manual  text summarizing, which is a time-consuming and labor 

intensive procedure, is gaining popularity, and is therefore  a major motivator for academic study. In today's age of  data overload, abstracting and summarizing huge texts is  critical. Over time, a variety of approaches for  summarizing text have been created. Traditional  approaches construct a summary directly as a result of the  duplication and omission of the document summary  connection. Deep learning algorithms have been  demonstrated to be useful in creating summaries. We  concentrate on deep learning-based text summarizing  algorithms that have been developed throughout time. 

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Published

2022-04-30

Issue

Vol. 9 No. 2 (2022): International Journal of Innovative Research in Engineering & Management (April )2022

Section

Articles

How to Cite

A Study of Implementation of Deep Learning Techniques for Text Summarization . (2022). International Journal of Innovative Research in Engineering & Management, 9(2), 18–28. Retrieved from https://acspublisher.com/journals/index.php/ijirem/article/view/10911