Abstract In the contemporary world, utilization of digital content has risen exponentially. For example, newspaper and web articles, status updates, advertisements etc. have become an integral part of our daily routine. Thus, there is a need to build an automated system to summarize such large documents of text in order to save time and effort. Although, there are summarizers for languages such as English since the work has started in the 1950s and at present has led it up to a matured stage but there are several languages that still need special attention such as Punjabi language. The Punjabi language is highly rich in morphological structure as compared to English and other foreign languages. In this work, we provide three phase extractive summarization methodology using neural networks. It induces compendious summary of Punjabi single text document. The methodology incorporates pre-processing phase that cleans the text; processing phase that extracts statistical and linguistic features; and classification phase. The classification based neural network applies an activation function- sigmoid and weighted error reduction-gradient descent optimization to generate the resultant output summary. The proposed summarization system is applied over monolingual Punjabi text corpus from Indian languages corpora initiative phase-II. The precision, recall and F-measure are achieved as 90.0%, 89.28% an 89.65% respectively which is reasonably good in comparison to the performance of other existing Indian languages’ summarizers.

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[51] Yong S., Abidin A., and Chen Y., “A Neural- Based Text Summarization System,” WIT Transactions on Information and Communication Technologies, vol. 37, pp. 185-192, 2006. 818 The International Arab Journal of Information Technology, Vol. 18, No. 6, November 2021 Arti Jain has received her Ph.D, in Computer Science and Engineering (2019) from Jaypee Institute of Information Technology, Noida, India. She has more than 18 years of teaching experience. Currently, she is working as Assistant Professor (Sr. Grade), CSE, JIIT, Noida, India. She is a member of IEEE, INSTICC, IAENG, IFERP and Life Member of TERA. She is reviewer of several reputed International Journals and TPC member of International Conferences. She has more than 20 publications in peer-reviewed International Journals, Book Chapters and International Conferences. Her research interests include Natural Language Processing, Machine Learning, Data Science, Deep Learning, Social Media Analysis, Big Data and Data Mining. Anuja Arora is working as Associate Professor in the Department of Computer Science and Engineering at Jaypee Institute of Information Technology, Noida, India. She is having academic experience of 15 years and industry experience of 1.5 years. She is Senior IEEE Member, ACM Member, SIAM Member, INSTICC and Life Member of IAENG. She is also Vice-Chair for the Delhi ACM-W Chapter. She has more than 70 research papers in peer-reviewed International Journals, Book Chapters, and International Conferences. She has supervised 3 Ph.D. thesis and 2 more are in progress. Her research interest includes Data Science, Deep Learning, Information Retrieval Systems, Machine Learning, Social Network Analysis, Software Testing and Web Intelligence. She is reviewer of many reputed and peer-reviewed IEEE transactions- TKDE, TNSM, IEEE Transaction of Cybernetics, Springer, IGI Global, Inderscience, and De Gruyter Journals. She has guided more than 17 M.Tech Thesis and around 100 B.Tech Projects. Divakar Yadav (SM’2017) is working as Associate Professor in the Department of Computer Science and Engineering at National Institute of Technology (NIT), Hamirpur (HP), India. He did his undergraduate in Computer Science and Engineering (1999), Post Graduate in Information Technology (2005) and PhD in Computer Science and Engineering (2010). He is Senior Member IEEE. He has also worked as Post-Doctoral Fellow at University of Carlos-III, Madrid, Spain from 2011-2012. He has supervised 5 PhD thesis and 22 Master dissertations. He has more than 20 years of teaching and research experience. He has published 85 research articles in reputed International Journals and Conference Proceedings. His area of research is Machine Learning and Information Retrieval. Jorge Morato has received his B.S. degree in Sciences from University of Alcala in 1992, and Ph.D. degree in Information Sciences from University Carlos III in 1999. Since 2000, he is researcher and professor with the Computer Science Department, Carlos III University, Spain. From 1991- 2016, he has had grants and fellowships from the Spanish National Research Council and the Spanish Government. He is the author of more than one hundred papers and book chapters. His research interests include NLP applications, Information Retrieval Algorithms, Web Positioning and Readability, and Knowledge Organization Systems. Amanpreet Kaur has received her B.E. degree in CSE from Guru Nanak Dev University, Amritsar, India, 2006, M.E. degree in Computer Science Engineering from NIT Jalandhar, 2009, and Ph.D. in Computer Science and Engineering from Jaypee Institute of Information Technology, Noida, Uttar Pradesh, India, 2020. She is currently working as Assistant Professor, CSE, Jaypee Institute of Information Technology, Noida (UP), India. Her research interests include Wireless Sensor Networks, Information Security and Performance Analysis.