Text Summarizer using NLP (Natural Language Processing)

Authors

  • Sheetal Patil Assistant Professor, Department of Computer Engineering, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune
  • Siddhi Khanna Student, Department of computer science & Engineering, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune India
  • Anurag Tiwari Student, Department of computer science & Engineering, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune India
  • Somay Trivedi Student, Department of computer science &Engineering, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune India
  • Avinash Pawar Associate Professor, Department of Mechanical Engineering, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune

DOI:

https://doi.org/10.37591/jocta.v12i3.855

Keywords:

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

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.

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Published

2021-12-16

Issue

Vol. 12 No. 3 (2021)

Section

Articles

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