Method to Evaluate Difficulty of Technical Terms

  • Yuta SudoEmail author
  • Toru Nakata
  • Toshikazu Kato
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9735)


We have developed an auto annotating system. To apply to the system, we conducted experiments about the method to evaluate difficulty of technical terms in documents by using data of Wikipedia. Based on a hypothesis that basic and easy terms appear frequently in Wikipedia, we surveyed relationship between subjective difficulty and appearance frequency in Wikipedia. As a result, we could classify technical terms into the easy term and the difficult term at the accuracy of 0.70.


Word clustering Automatic annotation Information assistance 



This work was partially supported by JSPS KAKENHI grants (No. 25240043) and TISE Research Grant of Chuo University.


  1. 1.
    Amano, S., Kondo, T.: Estimation of mental lexicon size with word familiarity database. In: Proceedings of International Conference on Spoken Language Processing, vol. 5, pp. 2119–2122 (1998)Google Scholar
  2. 2.
    Suchanek, F.M., Kasneci, G., Weikum, G.: Yago: a core of semantic knowledge. In: Proceedings of the 16th International Conference on World Wide Web, pp. 697–706. ACM, May 2007Google Scholar
  3. 3.
    Jiang, Z., Sun, G., Gu, Q., Bai, T., Chen, D.: A graph-based readability assessment method using word couplingGoogle Scholar
  4. 4.
    Sato, S., Matsuyoshi, S., Kondoh, Y.: Automatic assessment of Japanese text readability based on a textbook corpus. In: LREC, May 2008Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Graduate School of Science and EngineeringChuo UniversityTokyoJapan
  2. 2.National Institute of Advanced Industrial Science and Technology (AIST)TokyoJapan

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