Automatic Generation of Concept Maps based on Collection of Teaching Materials

Aliya Nugumanova, Madina Mansurova, Ermek Alimzhanov, Dmitry Zyryanov, Kurmash Apayev

2015

Abstract

The aim of this work is demonstration of usefulness and efficiency of statistical methods of text processing for automatic construction of concept maps of the pre-determined domain. Statistical methods considered in this paper are based on the analysis of co-occurrence of terms in the domain documents. To perform such analysis, at the first step we construct a term-document frequency matrix on the basis of which we can estimate the correlation between terms and the designed domain. At the second step we go on from the term-document matrix to the term-term matrix that allows to estimate the correlation between pairs of terms. The use of such approach allows to define the links between concepts as links in pairs which have the highest values of correlation. At the third step, we have to summarize the obtained information identifying concepts as nodes and links as edges of a graph and construct a concept map as resulting graph.

References

  1. Akhmed-Zaki, D., Mansurova M., Pyrkova A., 2014. Development of courses directed on formation of competences demanded on the market of IT technologies. In Proceedings of the 2014 Zone 1 Conference of the American Society for Engineering Education, pages 1-4. Scopus.
  2. Chen, N. S., Kinshuk Wei, C. W., and Chen, H. J., 2008. Mining e-learning domain concept map from academic articles. Computers & Education, 50(3): 1009-1021.
  3. Clariana, R. B., and Koul, R., 2004. A computer-based approach for translating text into concept map-like representations. In Proceedings of the First International Conference on Concept Mapping, Pamplona, Spain, pages 131-134.
  4. Allemang, D., and Hendler, J., 2011. Semantic Web for the Working Ontologist (Second Edition). Elsevier Inc.
  5. Deerwester, S. C., Dumais, S.T., Landauer, T.K., Furnas, G.W., Harshman, R.A., 1990. Indexing By Latent Semantic Analysis. Journal of the American Society of Information Science, 41(6): 391-407.
  6. Kornilakis H. et al., 2004. Using WordNet to support interactive concept map construction. In Proceedings of the IEEE International Conference Advanced Learning Technologies, pages 600-604. IEEE.
  7. Nugumanova, A., Issabayeva, D., Baiburin, Ye. Automatic generation of association thesaurus based on domainspecific text collection. In Proceedings of the 10th International Academic Conference, pages 529-538.
  8. Oliveira, A., Pereira, F.C., and Cardoso, A., 2001. Automatic reading and learning from text. Paper presented at the international symposium on artificial intelligence Kolhapur, India.
  9. Rajaraman K., and Tan, A.H., 2002. Knowledge Discovery from Texts: A Concept Frame Graph Approach. In Proceedings of the 11th Int. Conference on Information and Knowledge Management, pages 669-671.
  10. Sherman, R., 2003. Abstraction in concept map and coupled outline knowledge representations. Journal of Interactive Learning Research, Vol. 14.
  11. Valerio, A., Leake, D., 2008. Associating documents to concept maps in context. Paper presented at the third international conference on concept mapping, Finland.
  12. Valerio A., Leake D. B., Cañas A. J., 2012. Using automatically generated concept maps for document understanding: a human subjects experiment. In Proceedings of the 15 Int. Conference on Concept Mapping, pages 438-445.
  13. Villalon, J., Calvo, R. 2008. Concept map mining: A definition and a framework for its evaluation. In Proceedings of the International Conference on Web Intelligence and Intelligent Agent Technology, Vol. 3, pages 357-360.
  14. Villalon J., Calvo R., Montenegro R., 2010. Analysis of a gold standard for Concept Map Mining - How humans summarize text using concept maps. In Proceedings of the Fourth International Conference on Concept Mapping, pages 14-22.
  15. Zheng Z., X. Wu, and R. Srihari, 2004. Feature Selection for Text Categorization on Imbalanced Data. ACM SIGKDD Explorations Newsletter vol. 6:80-89.
  16. Zubrinic, K., Kalpic, D., and Milicevic, M., 2012. The automatic creation of concept maps from documents written using morphologically rich languages. Expert Systems with Applications, 39(16):12709-12718.
Download


Paper Citation


in Harvard Style

Nugumanova A., Mansurova M., Alimzhanov E., Zyryanov D. and Apayev K. (2015). Automatic Generation of Concept Maps based on Collection of Teaching Materials . In Proceedings of 4th International Conference on Data Management Technologies and Applications - Volume 1: DATA, ISBN 978-989-758-103-8, pages 248-254. DOI: 10.5220/0005554702480254


in Bibtex Style

@conference{data15,
author={Aliya Nugumanova and Madina Mansurova and Ermek Alimzhanov and Dmitry Zyryanov and Kurmash Apayev},
title={Automatic Generation of Concept Maps based on Collection of Teaching Materials},
booktitle={Proceedings of 4th International Conference on Data Management Technologies and Applications - Volume 1: DATA,},
year={2015},
pages={248-254},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005554702480254},
isbn={978-989-758-103-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of 4th International Conference on Data Management Technologies and Applications - Volume 1: DATA,
TI - Automatic Generation of Concept Maps based on Collection of Teaching Materials
SN - 978-989-758-103-8
AU - Nugumanova A.
AU - Mansurova M.
AU - Alimzhanov E.
AU - Zyryanov D.
AU - Apayev K.
PY - 2015
SP - 248
EP - 254
DO - 10.5220/0005554702480254