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Reseach Article

A Comparison on Techniques for Automatic Generation of Presentation Slides

by Biju P. Dais, Smitha C.S.
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 131 - Number 17
Year of Publication: 2015
Authors: Biju P. Dais, Smitha C.S.
10.5120/ijca2015907646

Biju P. Dais, Smitha C.S. . A Comparison on Techniques for Automatic Generation of Presentation Slides. International Journal of Computer Applications. 131, 17 ( December 2015), 1-6. DOI=10.5120/ijca2015907646

@article{ 10.5120/ijca2015907646,
author = { Biju P. Dais, Smitha C.S. },
title = { A Comparison on Techniques for Automatic Generation of Presentation Slides },
journal = { International Journal of Computer Applications },
issue_date = { December 2015 },
volume = { 131 },
number = { 17 },
month = { December },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume131/number17/23538-2015907646/ },
doi = { 10.5120/ijca2015907646 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:27:49.096633+05:30
%A Biju P. Dais
%A Smitha C.S.
%T A Comparison on Techniques for Automatic Generation of Presentation Slides
%J International Journal of Computer Applications
%@ 0975-8887
%V 131
%N 17
%P 1-6
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The automatic generation of presentation slides from technical articles is one of the most desired but under-researched area in the field of computing. Automated generation of slide contents from technical articles is much difficult than a typical text summarization process, since it requires the identification of all the crucial contents from the article and their arrangement in a systematic manner, thus making it a non trivial task. The process is considered to be one of the core applications of text mining. Automatic slide generators can be broadly classified based on NLP, Statistical Methods and Machine Learning. A detailed review of some of the most important automatic slide generation techniques from academic articles is presented and a brief comparison among the discussed techniques is given.

References
  1. V. Qazvinian, D. R. Radev, S. M. Mohammad, B. J. Dorr, D. M. Zajic, M. Whidby, and T. Moon, ”Generating extractive summaries of scientific paradigms”, J. Artif. Intell. Res., vol. 46, pp. 165- 201, 2013.
  2. V. Qazvinian and D. R. Radev, ”Scientific paper summarization using citation summary networks”, in Proc. 22nd Int. Conf. Comput. Linguistics-Volume 1, Aug. 2008, pp. 689- 696.
  3. N. Agarwal, K. Gvr, R. S. Reddy, and C. P. Rose, ”Towards multidocument summarization of scientific articles: Making interesting comparisons with SciSumm”, in Proc. Workshop Autom. Summarization Different Genres, Media, Lang., 2011, pp. 8-15.
  4. O. Yeloglu, M. Evangelos, and Z.-H. Nur, ”Multi-document summarization of scientific corpora”, in Proc. ACM Symp. Appl. Comput., 2011, pp. 252-258.
  5. R. Jha, A. Abu-Jbara, and D. Radev, ”A system for summarizing scientific topics starting from keywords”, ACM Comput. Surv, vol. 40, no. 3, p. 8, 2013.
  6. M. J. Conroy and D. P. O’leary, ”Text summarization via hidden Markov models”, in Proc. 24th Annu. Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval, 2001, pp. 406-407.
  7. D. Shen, J. T. Sun, H. Li, Q. Yang, and Z. Chen, ”Document summarization using conditional random fields”, in Proc. 20th Int. Joint Conf. Artif. Intell., 2007, vol. 7, pp. 2862- 2867.
  8. M. Utiyama and K. Hasida, ”Automatic slide presentation from semantically annotated documents”, in Proc. ACL Workshop Conf. Its Appl., 1999, pp. 25-30.
  9. Y. Yasumura, M. Takeichi, and K. Nitta, ”A support system for making presentation slides”, Trans. Japanese Soc. Artif. Intell., vol. 18, pp. 212-220, 2003.
  10. M. Sravanthi, C. R. Chowdary, and P. S. Kumar, ”SlidesGen: Automatic generation of presentation slides for a technical paper using summarization”, in Proc. 22nd Int. FLAIRS Conf., 2009, pp. 284-289.
  11. M. Sravanthi, C. R. Chowdary, and P. S. Kumar, ”QueSTS: A query specific text summarization approach”, in Proc. 21st Int. FLAIRS Conf., 2008, pp. 219-224.
  12. D. Marcu, ”From discourse structures to text summaries”, in Proc. ACL Workshop Intell. Scalable Text Summarization., 1997, vol. 97, pp. 82-88.
  13. T. Shibata and S. Kurohashi, ”Automatic slide generation based on discourse structure analysis”, in Proc. Int. Joint Conf. Natural Lang. Process., 2005, pp. 754-766.
  14. Gokul Prasad, K., Mathivanan, H., Jayaprakasam, M., and Geetha, T. V., ”Document summarization and information extraction for generation of presentation slides”, Advances in Recent Technologies in Communication and Computing, 2009. ARTCom’09. International Conference on. IEEE, 2009.
  15. Sariki, Tulasi Prasad, Bharadwaja Kumar, and Ramesh Ragala. ”Effective Classroom Presentation Generation Using Text Summarization”.
  16. S. M. A. Masum, M. Ishizuka, and M. T. Islam, ”Autopresentation: A multi-agent system for building automatic multi-modal presentation of a topic from world wide web information”, in Proc. IEEE/WIC/ACMInt. Conf. Intell. Agent Technol., 2005, pp. 246-249.
  17. S. M. A. Masum and M. Ishizuka, ”Making topic specific report and multimodal presentation automatically by mining the web resources”, in Proc. IEEE/WIC/ACM Int. Conf. Web Intell., 2006, pp. 240-246.
  18. Hu, Yue, and Xiaojun Wan. ”Ppsgen: learning to generate presentation slides for academic papers”, Proceedings of the Twenty-Third international joint conference on Artificial Intelligence. AAAI Press, 2013
  19. C. C. Chang and C. J. Lin. (2001), LIBSVM: A library for support vector machines, [Online]. Available: http://www.csie.ntu.edu. tw/ cjlin/libsvm
  20. L. Page, S. Brin, R. Motwani, and T. Winograd, ”The pagerank citation ranking: Bringing order to the web,” Stanford Digital Libraries, Stanford, CA, USA, Tech. Report: SIDLWP- 1999-0120, 1999.
  21. D. Radev, T. Allison, S. Blair-Goldensohn, J. Blitzer, A. Celebi, S.Dimitrov, E. Drabek, A. Hakim, W. Lam, D. Liu, J. Otterbacher, H. Qi, H. Saggion, S. Teufel, M. Topper, A. Winkel, and Z. Zhang,”MEAD - A platform for multidocument multilingual text summarization,” in Proc. 4th Int. Conf. Lang. Resources Eval., 2004, pp. 14.
  22. C. Y. Lin ”ROUGE: A package for automatic evaluation of summaries” in Proc.Workshop Text Summarization Branches Out, Post- Conf. Workshop ACL, 2004, pp. 2526. 6
Index Terms

Computer Science
Information Sciences

Keywords

Natural Language Processing Machine Learning Web Mining