• Chetana Varagantham
• Jannapureddy Srinija
• Yelleni Uday
• Kotha Madhumitha
• Dr. P. Venkateswara Rao

This Project represents the work related to Text Summarization. In this paper, we present a framework for summarizing the huge information. The proposed framework depends on highlight extraction from internet, utilizing both morphological elements and semantic data.Presently, where huge information is available on the internet, it is most important to provide the improved ways to extract the information quickly and most efficiently. It is very difficult for human beings to manually extract the summary of a large document of text.There are plenty of text materials available on the internet. So, there is a problem of searching for related documents from the number of documents available and absorbing related information from it. In essence to figure out the previous issues , the automatic text summarization is very much necessary.Text Summarization is the process of identifying the most important and meaningful information in a input document or set of related input documents and compressing all the inputs into a shorter version maintaining its over all objectives.

Machine Learning, Text Summarization, Natural Language Processing (NLP) ,Clustering, Tokens

"Text Summarization using NLP", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.c751-c756, May-2022, Available :http://www.jetir.org/papers/JETIR2205397.pdf

"Text Summarization using NLP", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. ppc751-c756, May-2022, Available at : http://www.jetir.org/papers/JETIR2205397.pdf