A Study of Implementation of Deep Learning Techniques for Text Summarization

Bilkeesa Akhter; Dr. Monika Mehra

doi:10.55524/ijirem.2022.9.2.3

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.

Keywords

Summarize text, Deep Learning Techniques, Effective, Automatization

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Cites this article as

B. Akhter, D. M. Mehra, "A Study of Implementation of Deep Learning Techniques for Text Summarization", International Journal of Innovative Research in Engineering & Management (IJIREM), Vol-9, Issue-2, Page No-18-28, 2022. Available from: https://doi.org/10.55524/ijirem.2022.9.2.3

Corresponding Author

Bilkeesa Akhter

M.Tech Scholar, Department of Electronics and Communication Engineering, RIMT University Mandi Gobingrah, Punjab, India

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