• Santhosh Voruganti
• U.Sairam

Text summarization refers to the technique of shortening long pieces of text. The intention is to create a coherent and fluent summary having only the main points outlined in the document. As the amount of information present on the internet is increasing, the need for summarization of long pieces of text is more important than ever, as reading long pieces of text may be time consuming. We aim to deploy the extractive summarization approach to achieve automated summarization. The extractive approach involves picking up the most important phrases and lines from the documents. It then combines all the important lines to create the summary. So, in this case, every line and word of the summary actually belongs to the original document which is summarized. Sentences are ranked by assigning weights and they are ranked based on their weights. Highly ranked sentences are extracted from the input document so it extracts important sentences which directs to a high-quality summary of the input document and store summary as a document. Briefly explaining, we aim to build a web application using flask which will be able to recognize and detect text from various sources, summarize it using Natural Language Processing (NLP) algorithms and libraries such as Natural Language Toolkit (NLTK), gensim, spacy, sumy and then save the summary in a document.

"TEXT SUMMARIZATION AND DETECTION BASED WEB APPLICATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 6, page no.c746-c758, June-2022, Available :http://www.jetir.org/papers/JETIR2206292.pdf

"TEXT SUMMARIZATION AND DETECTION BASED WEB APPLICATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 6, page no. ppc746-c758, June-2022, Available at : http://www.jetir.org/papers/JETIR2206292.pdf