A SURVEY AUTOMATIC TEXT SUMMARIZATION

Year 2017, , 205 - 213, 30.06.2017

Oguzhan Tas Farzad Kiyani

https://doi.org/10.17261/Pressacademia.2017.591

Abstract

Text
summarization is compress the source text into a diminished version conserving
its information content and overall meaning. Because of the great amount of the
information we are provided it and thanks to development of Internet
Technologies, text summarization has become an important tool for interpreting
text information. Text summarization methods can be classified into extractive
and abstractive summarization. An extractive summarization method involves
selecting sentences of high rank from the document based on word and sentence
features and put them together to generate summary. The importance of the
sentences is decided based on statistical and linguistic features of sentences.
An abstractive summarization is used to understanding the main concepts in a
given document and then expresses those concepts in clear natural language. In
this paper, gives comparative study of various text summarization techniques. 

Keywords

Text summarization, natural language processing, NLP, statistical approach

References

• E. H. Hovy, Automated Text Summarization. The Oxford Handbook of Computational Linguistics, Chapter 32, pages 583-598. Oxford University Press, 2005.
• I. Mani, D. House, G. Klein, The TIPSTER SUMMAC Text Summarization Evaluation. In Proceedings of EACL, 1999.
• H. P. Luhn, "The automatic creation of literature abstracts”, IBM Journal of Research and Development, vol. 2, pp. 159-165, 1958.
• U. Hahn, & I. Mani, “The challenges of automatic summarization” IEEE-Computer, 33(11), 29–36, 2000.
• V. Gupta, G.S. Lehal, “A survey of Text Summarization Extractive Techniques”, Journal of Emerging Technologies in Web Intelligence, Vol. 2, No.3, August 2010.
• S.A. Babar, P. D. Patil, “Improving Performance of Text Summarization”, International Conference on Information and Communication Technologies, ICICT, 2014.
• Sherry, P. Bhatia, “A Survey to Automatic Summarization Techniques”, International Journal of Engineering Research and General Science Volume 3, Issue 5, September-October, 2015.
• S. Karmakar, T. Lad, H. Chothani, A Review Paper on Extractive Techniques of Text Summarization, International Research Journal of Computer Science (IRJCS) Issue 1, Volume 2, 2015.
• F. C. Pembe and T. Güngör, “Automated Query-biased and Structure-preserving Text Summarization on Web Documents,” in Proceedings of the International Symposium on Innovations in Intelligent Systems and Applications, İstanbul, June 2007.
• G. Yihong, X. Liu. "Generic text summarization using relevance measure and latent semantic analysis." Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval, ACM, 2001.
• S. Alfayoumy, J. Thoppil, A Survey of Unstructured Text Summarization Techniques, International Journal of Advanced Computer Science and Applications, Vol. 5, No. 4, 2014.
• L. Suanmali, N. Salim, M. S. Binwahlan, “Fuzzy Logic Based Method for Improving Text Summarization”, International Journal of Computer Science and Information Security, Vol. 2, No. 1, 2009.
• P.Priya, G. and K Duraiswamy, “An Approach for Text Summarization Using Deep Learning Algorithm”, Journal of Computer Science, 19, 2014.
• Amy J.C. Trappey, Charles V. Trappey, “An R&D knowledge management method for patent document summarization” Industrial Management & Data Systems, vol.108. pp. 245-257. 2008.
• D. Ravichandran, P. Pantel, and E.H. Hovy, “Randomized Algorithms and NLP: Using Locality Sensitive Hash Functions for High Speed Noun Clustering”, Proceedings of the conference of the Association for Computational Linguistics (ACL), 2005.
• Khosrow Kaikhah, "Automatic Text Summarization with Neural Networks", in Proceedings of Second International Conference on intelligent systems, IEEE, 40-44, Texas, USA, June 2004.
• Khosrow Kaikhah, "Text Summarization using Neural Networks", Departments of Faculty Publications Computer Science, Texas State University, 2004.
• Sarda A.T., Kulkarni A.R., “Text Summarization using Neural Networks and Rhetorical Structure Theory”, International Journal of Advanced Research in Computer and Communication Engineering, 2015.
• W. C. Mann, S. Thompson, Rhetorical Structure Theory: Toward a functional theory of text organization. Text, 8 (3), 1988.
• F.Kyoomarsi, H. Khosravi, E. Eslami and P.H. Dehkordy, “Optimizing Text Summarization Based on Fuzzy Logic”, In proceedings of Seventh IEEE/ACIS International Conference on Computer and Information Science, IEEE, University of Shahid Bahonar Kerman, UK, 347352, 2008.
• S.A.Babar, S.A.Thorat, "Improving Text Summarization using Fuzzy Logic & Latent Semantic Analysis",International Journal of Innovative Research in Advanced Engineering (IJIRAE), 2014.
• J. Kupiec, J. Pedersen, and F. Chen, “A trainable document summarizer”, In Proceedings of the 18th ACMSIGIR Conference, pages 6873, 1995.
• E. Lahari, D.V.N.S. Kumar, M.Ubale, “A Comprehensive Survey on Feature Extraction in Text Summarization”, E Padma Lahari et al , Int.J.Computer Technology & Applications,Vol 5 (1),248-256, 2014.
• P.D. Patil, P.M. Mane, “An Overall Survey of Extractive Based Automatic Text Summarization Methods”, International Journal of Science and Research (IJSR) 2014.
• J. Conroy, D.P. O’leary, “Text Summarization via Hidden Markov Models and Pivoted QR Matrix Decomposition”, Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval 2001.
• C. Cığır, M. Kutlu, İ. Çiçekli, “Generic Text Summarization for Turkish”, The 24th International Symposium on Computer and Information Sciences, ISCIS 2009, 14-16 September 2009.
• C.Y. Lin, E.H. Hovy, “Automatic evaluation of summaries using n-gram co-occurrence statistics”, Proceedings of HLT-NAACL-2003, Edmenton, Canada, 2003.
• C.Y. Lin, “ROUGE: A Package for Automatic Evaluation of Summaries” In Proceedings of Workshop on Text Summarization of ACL, .Spain. 2004.
• L. Zadeh, “Fuzzy sets. Information Control” vol. 8, pp.338–353.1965.
• R. Witte and S. Bergler, “Fuzzy coreference resolution for summarization” In Proceedings of 2003 International Symposium on Reference Resolution and Its Applications to Question Answering and Summarization (ARQAS) 2003.
• P.D. Patil, N.J. Kalkurni, "Text Summarization Using Fuzzy Logic", International Journal of Innovative Research in Advanced Engineering (IJIRAE) Volume 1 Issue 3, 2014.
• S. Gholamrezazadeh, M. Salehi, B. Gholamzadeh “A Comprehensive Survey on Text Summarization Systems”, Computer Science and its Applications, 2009.