Experimental Evaluation and Approach of Enhancement in Generation of Automatic Unsupervised Extractive Text Summarization of Marathi Text By Using Machine Learning Algorithm
Apurva D. Dhawale
Apurva D. Dhawale
Dept. of Computer Science & IT, Dr. B. A. M. University, Aurangabad, India.
The Text summarization has immense importance in the arena of Natural Language Processing. The summarization can be done in two ways: abstractive and extractive text summarization. Here, the language is a vast query, because we have large number of national and international languages. By studying the literature, the Marathi language is chosen for this work and we are trying to make a framework where all the students giving competent examinations can have summarized Marathi e-news articles by using extractive text summarization. For this objective we have used TextRank algorithm which has proven very effective for different languages. This paper demonstrates the summarization techniques on Marathi e-news articles using Gensim Library of TextRank algorithm and comparative analysis of summaries generated by using both TextRank and ROUGH method.
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Apurva D. Dhawale, Sonali B. Kulkarni, Vaishali M. Kumbhakarna, “A Machine Learning Approach for Automatic Unsupervised Extractive Summarization of Marathi Text”, International Journal of Creative Research Thoughts (IJCRT), Volume 8, Issue 11 | ISSN: 2320-2882, November 2020.
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Apurva D. Dhawale
Apurva D. Dhawale
Dept. of Computer Science & IT, Dr. B. A. M. University, Aurangabad, India.
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Cite this article
Apurva D. Dhawale, Sonali B. Kulkarni, Vaishali M. Kumbhakarna, “Experimental Evaluation and Approach of Enhancement in Generation of Automatic Unsupervised Extractive Text Summarization of Marathi Text By Using Machine Learning Algorithm”, Journal of Machine and Computing, vol.2, no.1, pp. 026-032, January 2022. doi: 10.53759/7669/jmc202202004.
