Comparison Of Text Summarizer In Indian Languages

Text summarization is the process of extracting the relevant information from a source text keeps the significant information. Mainly two types of text summarization methods such as abstractive and extractive. The extractive summarization ranks all sentences and high scored sentences are selected as...

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Main Authors: D. K. Kanitha, D. Muhammad Noorul Mubarak, S. A. Shanavas
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Published: Zenodo 2018
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Online Access:https://dx.doi.org/10.5281/zenodo.1205087
https://zenodo.org/record/1205087
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topic Text Summarization, Extractive Methods, Abstractive Methods & Natural Language Processing
spellingShingle Text Summarization, Extractive Methods, Abstractive Methods & Natural Language Processing
D. K. Kanitha
D. Muhammad Noorul Mubarak
S. A. Shanavas
Comparison Of Text Summarizer In Indian Languages
topic_facet Text Summarization, Extractive Methods, Abstractive Methods & Natural Language Processing
description Text summarization is the process of extracting the relevant information from a source text keeps the significant information. Mainly two types of text summarization methods such as abstractive and extractive. The extractive summarization ranks all sentences and high scored sentences are selected as summary. The abstractive summarization understands the content of a document and re-state in few words. This paper discusses about various text summarization methods followed by the Indian languages. The existing algorithms are explained and then the merits and demerits are discussed. This paper also investigates which method is suitable for summarizing documents in Indian languages. : {"references": ["1.\tAqil Burney, Badar Sami, Nadeem Mahmood, Zain Abbas and Kashif Rizwan, (2012), \"Urdu Text Summarizer using Sentence Weight Algorithm for Word Processors\" Pakistan International Journal of Computer Applications (0975 \u2013 8887) Volume 46\u2013 No.19. 2.\tVishal Gupta, Gurpreet Singh Lehal, \"Features Selection and Weight learning for Punjabi Text Summarization\", International Journal of Engineering Trends and Technology- Volume2 Issue2- 2011. 3.\tJagadish S Kallimani., Srinivasa K, G., (2010) \"Information Retrieval by Text Summarization for an Indian Regional Language\", IEEE. 4.\tJayashree.R. Srikanta Murthy. & Sunny.K. (2011). \"Document summarization in kannada using keyword extraction\", CS & IT-CSCP, pp. 121-127. 5.\tEmbar, V.R., Deshpande, S.R., &Vaishnavi, A.K., (2013). \"sArAmsha- A Kannada Text Summarizer\", Advances in computing, ICACCI, International Conferencence on 22-25 Aug. 540-544, IEEE. 6.\tJ. S. Kallimani, K. G. Srinivasa and B. R. Eswara, \"Summarizing News Paper Articles: Experiments with Ontology Based, Customized, Extractive Text Summary and Word Scoring\", Journal of Cybernetics and Information Technologies, Bulgarian Academy of Sciences, vol. 12, pp. 34-50, 2012. 7.\tT. Islam and S. M. A. Masum, (2004). \"Bhasa: A Corpus Based Information Retrieval and Summarizer for Bengali Text,\" Macquarie University, Sydney, Australia. 8.\tK. Sarkar, (2012).\"Bengali text summarization by sentence extraction,\" In Proceedings of International Conference on Business and Information Management (ICBIM-2012), NIT Durgapur, pp. 233-245. 9.\tK. Sarkar, (2012). \"An approach to summarizing Bengali news documents,\" In proceedings of the International Conference on Advances in Computing, Communications and Informatics, ACM, pp. 857-862. 10.\tA. Das and S. Bandyopadhyay, (2010). \"Topic-Based Bengali Opinion Summarization\", International Conference COILING '10, Beijing, pp. 232\u2013240. 11.\tSankar K, Vijay Sundar Ram R and Sobha Lalitha Devi, (2011). Text Extraction for an Agglutinative Language, Problems of Parsing in Indian Languages, Special Volume. 12.\tR. C. Balabantaray, B. Sahoo, D. K. Sahoo, M. Swain, (2012). Odia Text Summarization using Stemmer, International Journal of Applied Information Systems (IJAIS) \u2013 ISSN: 2249-0868, Volume 1\u2013 No.3, 2012. 13.\tNilofar Mulla, Shital K. Dhamal, (2016). \"A Survey of Text Summarization Techniques for Different Indian Regional Languages\", International Journal of Innovative Research in Computer and Communication Engineering Vol. 4, Issue 8. 14.\tDhanya, P. M., and M. Jathavedan, (2013). NCILC seminar proceedings. 15.\tRenjith. S. R, Sony.P, (2015). \"An automatic text summarization for Malayalam using sentence extraction\", IRF International Conference, ISBN: 978-93-85465-35-2. 16.\tAjmal E.B, Posna P Haron, (2015) \"Summarization of Malayalam Document Using Relevance of Sentences\" International Journal of Latest Research in Engineering and Technology, Volume I Issue 6 pp 08-13. 17.\tAnjana T G (2017). \"Summarizing Malayalam News Articles Using Topic Modeling\" International Journal of Innovations & Advancement in Computer Science IJIACS ISSN 2347 \u2013 8616 Volume 6, Issue 10. 18.\tFurnas, G.W., Landauer, T.K., Gomez, L.M., and Dumais, S.T. (1983). Statistical semantics: Analysis of the potential performance of key-word information systems. Bell System Technical Journal, 62(6), 1753-1806. 19.\tU. Garain, A. K. Datta, U Bhattacharya and S.K. Parui, (2006), Summarization of JBIG2 Compressed Indian Textual Images,\u2016 Proceeding of 18th International Conference onPattern Recognition (ICPR'06), IEEE, Kolkata, India, Vol. 3, Pp. 344-347, 2006. 20.\tChetan Thaokar And Latesh Malik \" Test Model for Summarizing Hindi Text using Extraction Method\"In Proceedings of 2013 IEEE Conference on Information and Communication Technologies (ICT 2013 21.\tKumar, K. Vimal, and Divakar Yadav. \"An Improvised Extractive Approach to Hindi Text Summarization.\" In Information Systems Design and Intelligent Applications, pp. 291-300, Springer India, 2015 22.\tKeyan, M.K., & Srinivasagan,K.G., \"Multi-Document and Multi-Lingual Summarization using Neural Networks\", Proceedings of International Conference on Recent Trends pp. 11-14, 2012. 23.\tM. Banu, C. Karthika, P. Sudarmani and T.V. Geetha, \"Tamil Document Summarization Using Semantic Graph Method\", International Conference on Computational Intelligence and Multimedia Applications, IEEE, pp. 128-134, 2007."]}
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author D. K. Kanitha
D. Muhammad Noorul Mubarak
S. A. Shanavas
author_facet D. K. Kanitha
D. Muhammad Noorul Mubarak
S. A. Shanavas
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title Comparison Of Text Summarizer In Indian Languages
title_short Comparison Of Text Summarizer In Indian Languages
title_full Comparison Of Text Summarizer In Indian Languages
title_fullStr Comparison Of Text Summarizer In Indian Languages
title_full_unstemmed Comparison Of Text Summarizer In Indian Languages
title_sort comparison of text summarizer in indian languages
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spelling ftdatacite:10.5281/zenodo.1205087 2023-05-15T18:14:17+02:00 Comparison Of Text Summarizer In Indian Languages D. K. Kanitha D. Muhammad Noorul Mubarak S. A. Shanavas 2018 https://dx.doi.org/10.5281/zenodo.1205087 https://zenodo.org/record/1205087 unknown Zenodo https://dx.doi.org/10.5281/zenodo.1205086 Open Access Creative Commons Attribution 4.0 https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess CC-BY Text Summarization, Extractive Methods, Abstractive Methods & Natural Language Processing Text Journal article article-journal ScholarlyArticle 2018 ftdatacite https://doi.org/10.5281/zenodo.1205087 https://doi.org/10.5281/zenodo.1205086 2021-11-05T12:55:41Z Text summarization is the process of extracting the relevant information from a source text keeps the significant information. Mainly two types of text summarization methods such as abstractive and extractive. The extractive summarization ranks all sentences and high scored sentences are selected as summary. The abstractive summarization understands the content of a document and re-state in few words. This paper discusses about various text summarization methods followed by the Indian languages. The existing algorithms are explained and then the merits and demerits are discussed. This paper also investigates which method is suitable for summarizing documents in Indian languages. : {"references": ["1.\tAqil Burney, Badar Sami, Nadeem Mahmood, Zain Abbas and Kashif Rizwan, (2012), \"Urdu Text Summarizer using Sentence Weight Algorithm for Word Processors\" Pakistan International Journal of Computer Applications (0975 \u2013 8887) Volume 46\u2013 No.19. 2.\tVishal Gupta, Gurpreet Singh Lehal, \"Features Selection and Weight learning for Punjabi Text Summarization\", International Journal of Engineering Trends and Technology- Volume2 Issue2- 2011. 3.\tJagadish S Kallimani., Srinivasa K, G., (2010) \"Information Retrieval by Text Summarization for an Indian Regional Language\", IEEE. 4.\tJayashree.R. Srikanta Murthy. & Sunny.K. (2011). \"Document summarization in kannada using keyword extraction\", CS & IT-CSCP, pp. 121-127. 5.\tEmbar, V.R., Deshpande, S.R., &Vaishnavi, A.K., (2013). \"sArAmsha- A Kannada Text Summarizer\", Advances in computing, ICACCI, International Conferencence on 22-25 Aug. 540-544, IEEE. 6.\tJ. S. Kallimani, K. G. Srinivasa and B. R. Eswara, \"Summarizing News Paper Articles: Experiments with Ontology Based, Customized, Extractive Text Summary and Word Scoring\", Journal of Cybernetics and Information Technologies, Bulgarian Academy of Sciences, vol. 12, pp. 34-50, 2012. 7.\tT. Islam and S. M. A. Masum, (2004). \"Bhasa: A Corpus Based Information Retrieval and Summarizer for Bengali Text,\" Macquarie University, Sydney, Australia. 8.\tK. Sarkar, (2012).\"Bengali text summarization by sentence extraction,\" In Proceedings of International Conference on Business and Information Management (ICBIM-2012), NIT Durgapur, pp. 233-245. 9.\tK. Sarkar, (2012). \"An approach to summarizing Bengali news documents,\" In proceedings of the International Conference on Advances in Computing, Communications and Informatics, ACM, pp. 857-862. 10.\tA. Das and S. Bandyopadhyay, (2010). \"Topic-Based Bengali Opinion Summarization\", International Conference COILING '10, Beijing, pp. 232\u2013240. 11.\tSankar K, Vijay Sundar Ram R and Sobha Lalitha Devi, (2011). Text Extraction for an Agglutinative Language, Problems of Parsing in Indian Languages, Special Volume. 12.\tR. C. Balabantaray, B. Sahoo, D. K. Sahoo, M. Swain, (2012). Odia Text Summarization using Stemmer, International Journal of Applied Information Systems (IJAIS) \u2013 ISSN: 2249-0868, Volume 1\u2013 No.3, 2012. 13.\tNilofar Mulla, Shital K. Dhamal, (2016). \"A Survey of Text Summarization Techniques for Different Indian Regional Languages\", International Journal of Innovative Research in Computer and Communication Engineering Vol. 4, Issue 8. 14.\tDhanya, P. M., and M. Jathavedan, (2013). NCILC seminar proceedings. 15.\tRenjith. S. R, Sony.P, (2015). \"An automatic text summarization for Malayalam using sentence extraction\", IRF International Conference, ISBN: 978-93-85465-35-2. 16.\tAjmal E.B, Posna P Haron, (2015) \"Summarization of Malayalam Document Using Relevance of Sentences\" International Journal of Latest Research in Engineering and Technology, Volume I Issue 6 pp 08-13. 17.\tAnjana T G (2017). \"Summarizing Malayalam News Articles Using Topic Modeling\" International Journal of Innovations & Advancement in Computer Science IJIACS ISSN 2347 \u2013 8616 Volume 6, Issue 10. 18.\tFurnas, G.W., Landauer, T.K., Gomez, L.M., and Dumais, S.T. (1983). Statistical semantics: Analysis of the potential performance of key-word information systems. Bell System Technical Journal, 62(6), 1753-1806. 19.\tU. Garain, A. K. Datta, U Bhattacharya and S.K. Parui, (2006), Summarization of JBIG2 Compressed Indian Textual Images,\u2016 Proceeding of 18th International Conference onPattern Recognition (ICPR'06), IEEE, Kolkata, India, Vol. 3, Pp. 344-347, 2006. 20.\tChetan Thaokar And Latesh Malik \" Test Model for Summarizing Hindi Text using Extraction Method\"In Proceedings of 2013 IEEE Conference on Information and Communication Technologies (ICT 2013 21.\tKumar, K. Vimal, and Divakar Yadav. \"An Improvised Extractive Approach to Hindi Text Summarization.\" In Information Systems Design and Intelligent Applications, pp. 291-300, Springer India, 2015 22.\tKeyan, M.K., & Srinivasagan,K.G., \"Multi-Document and Multi-Lingual Summarization using Neural Networks\", Proceedings of International Conference on Recent Trends pp. 11-14, 2012. 23.\tM. Banu, C. Karthika, P. Sudarmani and T.V. Geetha, \"Tamil Document Summarization Using Semantic Graph Method\", International Conference on Computational Intelligence and Multimedia Applications, IEEE, pp. 128-134, 2007."]} Text sami DataCite Metadata Store (German National Library of Science and Technology) Dumais ENVELOPE(-64.500,-64.500,-85.033,-85.033) Gomez ENVELOPE(-58.795,-58.795,-62.196,-62.196) Indian Landauer ENVELOPE(-67.800,-67.800,-67.067,-67.067)