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1703633 Vol 6 · Issue 1 Download Paper

Text Summarizer Using NLP (Natural Language Processing)

Aakash Srivastava Himanshu Daharwal Kamal Chauhan Nikhil Mukati Pranoti Shrikant Kavimandan

Subject area: Science,Engineering and Technology  ·  Area of research: Computer Science and Business System

Abstract

Enormous amounts of information are available online on the World Wide Web. To access information from databases, search engines like Google and Yahoo were created. Because the amount of electronic information is growing every day, the real outcomes have not been reached. As a result, automated summarization is in high demand. Automatic summary takes several papers as input and outputs a condensed version, saving both information and time. The study was conducted in a single document and resulted in numerous publications. This report focuses on the frequency-based approach for text summarization.

Keywords

Automatic summarization, Extractive, frequency-based, Natural Language Processing.

How to cite this paper

Aakash Srivastava, Himanshu Daharwal, Kamal Chauhan, Nikhil Mukati, Pranoti Shrikant Kavimandan "Text Summarizer Using NLP (Natural Language Processing)" Iconic Research And Engineering Journals Volume 6 Issue 1 2022 Page 211-216
Aakash Srivastava, Himanshu Daharwal, Kamal Chauhan, Nikhil Mukati, Pranoti Shrikant Kavimandan "Text Summarizer Using NLP (Natural Language Processing)" Iconic Research And Engineering Journals, vol. 6, no. 1, Jul. 2022
Aakash Srivastava, Himanshu Daharwal, Kamal Chauhan, Nikhil Mukati, Pranoti Shrikant Kavimandan (2022). Text Summarizer Using NLP (Natural Language Processing). Iconic Research And Engineering Journals, 6(1).
Aakash Srivastava, Himanshu Daharwal, Kamal Chauhan, Nikhil Mukati, Pranoti Shrikant Kavimandan "Text Summarizer Using NLP (Natural Language Processing)" Iconic Research And Engineering Journals, vol. 6, no. 1, Jul. 2022.
@article{1703633,
      author = {Aakash Srivastava, Himanshu Daharwal, Kamal Chauhan, Nikhil Mukati, Pranoti Shrikant Kavimandan},
      title = {Text Summarizer Using NLP (Natural Language Processing)},
      journal = {Iconic Research And Engineering Journals},
      year = {2022},
      volume = {6},
      number = {1},
      pages = {211-216},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1703633.pdf},
      abstract = {Enormous amounts of information are available online on the World Wide Web. To access information from databases, search engines like Google and Yahoo were created. Because the amount of electronic information is growing every day, the real outcomes have not been reached. As a result, automated summarization is in high demand. Automatic summary takes several papers as input and outputs a condensed version, saving both information and time. The study was conducted in a single document and resulted in numerous publications. This report focuses on the frequency-based approach for text summarization.},
      keywords = {Automatic summarization, Extractive, frequency-based, Natural Language Processing.},
      month = {July},
  }