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.
Citations
IRE Journals:
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
IEEE:
Aakash Srivastava , Himanshu Daharwal , Kamal Chauhan , Nikhil Mukati , Pranoti Shrikant Kavimandan
"Text Summarizer Using NLP (Natural Language Processing)" Iconic Research And Engineering Journals, 6(1)
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