Text Summarizer with Sequence-To-Sequence Model

Authors

  • Veluru Karthik Reddy Dept. of CS&IT Koneru Lakshmaiah Eduaction Foundation, Vaddeshwaram A.P,India
  • Vanapalli Durga Prashanth Dept. of CS&IT Koneru Lakshmaiah Eduaction Foundation, Vaddeshwaram A.P,India
  • R. Shiva Rama Krishna Dept .of CS&IT Koneru Lakshmaiah Education Foundation,Vaddeshwaram ,A.P,India
  • Naidu Sri lekha Dept.t of CS&IT Koneru Lakshmaiah Education Foundation, Vaddeshwaram ,A.P, India
  • Jyothi N. M. Dept. of CSE,Koneru Lakshmaiah Education Foundation, Vaddeswaram,AP India

Keywords:

Decoder, Encoder, Natural Language Processing, Sequence-to-sequence model, Text summarization

Abstract

The utilization of a Sequence-to-Sequence model in the realm of automated text summarization has evolved into an indispensable instrument for the effective handling of prodigious volumes of textual data.This method uses a decoder to produce a summary of the content after processing the input text through an encoder. The attention method, which aids the model in prioritizing essential information during summary creation, is the main innovation. To teach the model how to produce effective summaries, it must be exposed to pairs of source texts and their matching target summaries. This model is useful for a variety of natural language processing applications since it can efficiently summarize new, unread content when used in the actual world. In addition, the Sequence-to-Sequence model has proven effective in several applications, such as content extraction, document summarization, and news item summarization. By drawing crucial insights from large amounts of textual data, this technology responds to the growing problem of information overload by enabling more effective information retrieval and decision-making procedures.

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Published

24.03.2024

How to Cite

Reddy, V. K. ., Prashanth, V. D. ., Krishna, R. S. R. ., lekha, N. S. ., & N. M. , J. . (2024). Text Summarizer with Sequence-To-Sequence Model . International Journal of Intelligent Systems and Applications in Engineering, 12(19s), 525–530. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5095

Issue

Vol. 12 No. 19s (2024)

Section

Research Article

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