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Machine Learning Approach to the Process of Question Generation

  • Miroslav BlštákEmail author
  • Viera Rozinajová
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10415)

Abstract

In this paper, we introduce an interactive approach to generation of factual questions from unstructured text. Our proposed framework transforms input text into structured set of features and uses them for question generation. Its learning process is based on combination of machine learning techniques known as reinforcement learning and supervised learning. Learning process starts with initial set of pairs formed by declarative sentences and assigned questions and it continuously learns how to transform sentences into questions. Process is also improved by feedback from users regarding already generated questions. We evaluated our approach and the comparison with state-of-the-art systems shows that it is a perspective way for research.

Keywords

Question generation Machine learning Computer assisted learning 

Notes

Acknowledgments

The work reported here was supported by the Scientific Grant Agency of Slovak Republic (VEGA) under the grants No. VG 1/0752/14, VG 1/0646/15, ITMS 26240120039 and STU Grant scheme for Support of Young Researchers.

References

  1. 1.
    Blšták, M., Rozinajová, V.: Automatic question generation based on analysis of sentence structure. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds.) TSD 2016. LNCS, vol. 9924, pp. 223–230. Springer, Cham (2016). doi: 10.1007/978-3-319-45510-5_26 Google Scholar
  2. 2.
    Curto, S., Mendes, A.C., Coheur, L.: Question generation based on lexico-syntactic patterns learned from the web. Dialogue Discourse 3(2), 147–175 (2012)CrossRefGoogle Scholar
  3. 3.
    Heilman, M., Smith, N.A.: Question generation via overgenerating transformations and ranking. Technical report, DTIC Document (2009)Google Scholar
  4. 4.
    Huang, Y.T., Tseng, Y.M., Sun, Y.S., Chen, M.C.: Tedquiz: Automatic quiz generation for ted talks video clips to assess listening comprehension. In: 2014 IEEE 14th International Conference on Advanced Learning Technologies, pp. 350–354, July 2014Google Scholar
  5. 5.
    Huang, Y.T., Chen, M.C., Sun, Y.S.: Personalized automatic quiz generation based on proficiency level estimation. In: 20th International Conference on Computers in Education (2012)Google Scholar
  6. 6.
    Hussein, H., Elmogy, M., Guirguis, S.: Automatic english question generation system based on template driven scheme. Int. J. Comput. Sci. Issues (IJCSI) 11(6), 45–53 (2014)Google Scholar
  7. 7.
    Le, N.T., Pinkwart, N.: Question generation using wordnet. In: Proceedings of the 22nd International Conference on Computers in Education (2014)Google Scholar
  8. 8.
    Lee, J., Seneff, S.: Automatic generation of cloze items for prepositions. In: INTERSPEECH, pp. 2173–2176 (2007)Google Scholar
  9. 9.
    Lin, Y.C., Sung, L.C., Chen, M.C.: An automatic multiple-choice question generation scheme for English adjective understanding. In: Workshop on Modeling, Management and Generation of Problems/Questions in eLearning, The 15th International Conference on Computers in Education, ICCE 2007, pp. 137–142 (2007)Google Scholar
  10. 10.
    Navarro, G.: A guided tour to approximate string matching. ACM Comput. Surv. (CSUR) 33(1), 31–88 (2001)CrossRefGoogle Scholar
  11. 11.
    Rakangor, S., Ghodasara, Y.: Automatic fill in the blanks with distractor generation from given corpus. Int. J. Comput. Appl. 105(9) (2014)Google Scholar
  12. 12.
    Rodrigues, H., Coheur, L., Nyberg, E.: QGASP: a framework for question generation based on different levels of linguistic information. In: The 9th International Natural Language Generation conference, p. 242 (2016)Google Scholar
  13. 13.
    Rus, V., Wyse, B., Piwek, P., Lintean, M.C., Stoyanchev, S., Moldovan, C.: A detailed account of the first question generation shared task evaluation challenge. Dialogue Discourse 3(2), 177–204 (2012)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Faculty of Informatics and Information Technologies, Institute of Informatics, Information Systems and Software EngineeringSlovak University of Technology in BratislavaBratislavaSlovakia

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