Assessing Word Difficulty for Quiz-Like Game

  • Jakub Jagoda
  • Tomasz BoińskiEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10546)


Mappings verification is a laborious task. Our research aims at providing a framework for manual verification of mappings using crowdsourcing approach. For this purpose we plan on implementing a quiz like game. For this purpose the mappings have to be evaluated in terms of difficulty to better present texts in respect of game levels. In this paper we present an algorithm for assessing word difficulty. Three approaches are presented and experimental results are shown. Plans for future works are also provided.


  1. 1.
    Korytkowski, R., Szymanski, J.: Collaborative approach to WordNet and Wikipedia integration. In: The Second International Conference on Advanced Collaborative Networks, Systems and Applications, COLLA, pp. 23–28 (2012)Google Scholar
  2. 2.
    Szymański, J.: Mining relations between Wikipedia categories. In: Zavoral, F., Yaghob, J., Pichappan, P., El-Qawasmeh, E. (eds.) NDT 2010. CCIS, vol. 88, pp. 248–255. Springer, Heidelberg (2010). CrossRefGoogle Scholar
  3. 3.
    Szymański, J.: Words context analysis for improvement of information retrieval. In: Nguyen, N.-T., Hoang, K., Jȩdrzejowicz, P. (eds.) ICCCI 2012. LNCS (LNAI), vol. 7653, pp. 318–325. Springer, Heidelberg (2012). CrossRefGoogle Scholar
  4. 4.
    Szymański, J., Duch, W.: Self organizing maps for visualization of categories. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds.) ICONIP 2012. LNCS, vol. 7663, pp. 160–167. Springer, Heidelberg (2012). CrossRefGoogle Scholar
  5. 5.
    Von Ahn, L.: Games with a purpose. Computer 39(6), 92–94 (2006)CrossRefGoogle Scholar
  6. 6.
    Von Ahn, L., Dabbish, L.: Designing games with a purpose. Commun. ACM 51(8), 58–67 (2008)Google Scholar
  7. 7.
    Biuro Prasowe Samsung Electronics Polska Sp. z o.o.: Prawie połowa Polaków gra codziennie w gry wideo (in Polish)Google Scholar
  8. 8.
    Wightman, D.: Crowdsourcing human-based computation. In: Proceedings of the 6th Nordic Conference on Human-Computer Interaction: Extending Boundaries, pp. 551–560. ACM (2010)Google Scholar
  9. 9.
    Boiński, T.: Game with a purpose for mappings verification. In: 2016 Federated Conference on Computer Science and Information Systems (FedCSIS), pp. 405–409. IEEE (2016)Google Scholar
  10. 10.
    Binkley, M.R.: New ways of assessing text difficulty. Readability: Its past, present and future, pp. 98–120 (1988)Google Scholar
  11. 11.
    Kauchak, D., Leroy, G., Hogue, A.: Measuring text difficulty using parse-tree frequency. J. Assoc. Inf. Sci. Technol. 68, 2088–2100 (2017)CrossRefGoogle Scholar
  12. 12.
    Crossley, S.A., Greenfield, J., McNamara, D.S.: Assessing text readability using cognitively based indices. Tesol Q. 42(3), 475–493 (2008)CrossRefGoogle Scholar
  13. 13.
    Breland, H.M.: Word frequency and word difficulty: a comparison of counts in four corpora. Psychol. Sci. 7(2), 96–99 (1996)CrossRefGoogle Scholar
  14. 14.
    Carroll, J.B.: An alternative to Juilland’s usage coefficient for lexical frequencies. ETS Res. Rep. Ser. 1970(2), 1–15 (1970)Google Scholar
  15. 15.
    Inc., T.: Twinword API (2011). Accessed 10 May 2017
  16. 16.
    Kincaid, J.P., Fishburne Jr, R.P., Rogers, R.L., Chissom, B.S.: Derivation of new readability formulas (automated readability index, fog count and flesch reading ease formula) for navy enlisted personnel. Technical report, DTIC Document (1975)Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Department of Computer Architecture, Faculty of Electronics, Telecommunication and InformaticsGdańsk University of TechnologyGdańskPoland

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