• Piyush Patil
• Sanket Sutar
• Rupesh Deshmukh
• Prathamesh Chaudhari
• Prof. Priti Vaidya

Manual summarization of huge documents of texts is tedious and error-prone. Also, the results in such quite summarization may cause different results for a selected document. Thus, Automatic text summarization has become important because of the tremendous growth of knowledge and data. It chooses the foremost informative neighbourhood of text and forms summaries that reveal the foremost purpose of the given document. It yields a summary produced by a summarization system which allows readers to understand the content of the document instead of reading each and every individual document. The aim of Text Summarizer is to supply the meaning of the text in fewer words and sentences. Summarization is often categorized into Abstractive and Extractive. This project is based on an extractive concept implemented on the studied models. Numerous text summarization systems are there today for English or other languages. But when it involves Indian languages, we observe an inadequate number of automatic summarizers. Our efforts during this direction are mainly for developing an automatic text summarizer for the Marathi Language. We glance forward to gauge the obtained summaries using the ROUGE metric.

summarizer, extractive, Marathi, text rank, features extraction.

"Marathi Text Summarizer using Text rank algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.d479-d483, June-2021, Available :http://www.jetir.org/papers/JETIR2106469.pdf

"Marathi Text Summarizer using Text rank algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppd479-d483, June-2021, Available at : http://www.jetir.org/papers/JETIR2106469.pdf