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Guided Generation of Pedagogical Concept Maps from the Wikipedia

, Helsinki University of Technology, Finland

E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, in Vancouver, Canada ISBN 978-1-880094-76-1 Publisher: Association for the Advancement of Computing in Education (AACE), San Diego, CA


We propose a new method for guided generation of concept maps from open access online knowledge resources such as Wikies. Based on this method we have implemented a prototype extracting semantic relations from sentences surrounding hyperlinks in the Wikipedia’s articles and letting a learner to create customized learning objects in real-time based on collaborative recommendations considering her earlier knowledge. Open source modules enable pedagogically motivated exploration in Wiki spaces, corresponding to an intelligent tutoring system. The method extracted compact noun–verb–noun phrases, suggested for labeling arcs between nodes that were labeled with article titles. On average, 80 percent of these phrases were useful while their length was only 20 percent of the length of the original sentences. Experiments indicate that even simple analysis algorithms can well support user-initiated information retrieval and building intuitive learning objects that follow the learner’s needs.


Lahti, L. (2009). Guided Generation of Pedagogical Concept Maps from the Wikipedia. In T. Bastiaens, J. Dron & C. Xin (Eds.), Proceedings of E-Learn 2009--World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 1741-1750). Vancouver, Canada: Association for the Advancement of Computing in Education (AACE). Retrieved March 21, 2019 from .


View References & Citations Map


  1. Apache Commons (2009). HttpClient project. Http://
  2. Buriol, L., Castillo, C., Donato, D., Leonardi, S., & Millozzi, S. (2006). Temporal analysis of the Wikigraph. Proc. IEEE/WIC/ACM International Conference on Web Intelligence, 45 – 51.
  3. Dey,L., Abulaish, M., Goyel, R., & Jahiruddin (2007). Semantic integration of information through relation mining application to bio-medical text processing. LNCS 4815, 365-372.
  4. Eppler, M., & Burkard, R. (2006). Knowledge visualization– towards a new discipline and its fields of application. In David G. Schwartz (ed.), Encyclopedia of Knowledge Management. Idea Group Inc.
  5. Falsicon (2009). Page hits per day for in year 2008. Based on 210 analysed days, requests counted by Squid servers. Http:// (accessed May 2009)
  6. Fellbaum, C. (ed.) (1998). WordNet – an electronic lexical database. MIT Press.
  7. Gabrilovich, E., & Markovitch, S. (2009). Wikipedia-based semantic interpretation for natural language processing. Journal of Artificial Intelligence Research 34, 443 – 498.
  8. Gladun, A., Rogushinab, J., García-Sanchezc, F., Martínez-Béjarc, R., & Fernández-Breisd, J. (2007). An application of intelligent techniques and semantic web technologies in e-learning environments. Journal of Expert Systems with Applications, 36, 1922-1931-1749-–
  9. Gregorowicz, A., & Kramer, M. (2006). Mining a large-scale term-concept network from Wikipedia. Technical report. MITRE Corporation, Bedford, MA, USA.
  10. Hammond, T., Hannay, T., Lund, B., & Scott, J. (2005). Social bookmarking tools (I)-a general review. D-Lib Magazine 11(4).
  11. Higashinaka, R., Dohsaka, K., & Isozaki, H. (2007). Learning to rank definitions to generate quizzes for interactive information presentation. In Companion volume to Proc. 45th Annual Meeting of the Association for Computational Linguistics, 117 – 120.
  12. Hoffmann, R., Amershi, S., Patel, K., Wu, F., Fogarty, J., Weld, D. (2009). Amplifying community content creation using mixed-initiative information extraction. Proc. Conference on Human Factors in Computing Systems 2009.
  13. Jijkoun, V., & De Rijke, M. (2006). Overview of the WiQA task at CLEF 2006. Proc. 7th Workshop of the CrossLanguage Evaluation Forum (CLEF 2006), LNCS 4730, 265 – 274.
  14. Kaisser, M. (2008). The QuALiM question answering demo: supplementing answers with paragraphs drawn from Wikipedia. Proc. Annual Meeting of the Association for Computational Linguistics combined with the Human Language Technology Conference (ACL-08 HLT), Demo Session, 32 – 35.
  15. Kumar, A. (2006). Using Enhanced Concept Map for Student Modeling in Programming Tutors. Proc. Florida Artificial Intelligence Research Society Conference (FLAIRS 2006).
  16. Lahti, L. (2009). Assistive tool for collaborative learning of conceptual structures. Proc. Human Computer Interaction International 2009, Vol. 3, LNCS 5616, 53 – 62.
  17. Lahti, L., & Tarhio, J. (2008). Semi-automated map generation for concept gaming. Proc. IADIS International Conference Gaming 2008 (part of MCCSIS 2008), 36-43.
  18. Laurence, S., & Margolis, E. (1999). Concepts and cognitive science. In Concepts: Core Readings, MIT Press, 3 – 81.
  19. Lenat, D. (1995). Cyc: A large-scale investment in knowledge infrastructure. Communications of the ACM, 38(11).
  20. Milne, D., & Witten, I. (2008). Learning to link with Wikipedia. Proc. ACM Conference on Information and Knowledge Management (CIKM ’ 2008).
  21. Medelyan, O., Milne, D., Legg, C., & Witten, I. (2009). Mining meaning from Wikipedia. International Journal of Human-Computer Studies. 67(9), 716 – 754.
  22. Muthesius, T., Legois, D., Ramus, C., & Bourdu, S. (2008). Wikipedia-Roll browsing application. Http://
  23. Nakayama, K. (2008). Extracting structured knowledge for semantic web by mining Wikipedia. Proc. 7th International Semantic Web Conference (ISWC2008), Posters& Demos.
  24. Nakayama, K., Hara, T., & Nishio, S. (2008). Wikipedia link structure and text mining for semantic relation extraction– towards a huge scale global Web ontology. Proc. SemSearch 2008, CEUR Workshop, 59 – 73.
  25. Nasharuddin, N., Hamid, J., Ibrahim, H., Selamat, M., Abdullah, R., & Isa, W. (2008). Visualizer for concept relations in an automatic meaning extraction system. VINE: The journal of information and knowledge management systems, 38 (2), 232 – 240.
  26. Nauman, M., Khan, S., Amin, M., & Hussain, F. (2008). Resolving lexical ambiguities in folksonomy based search systems through commonsense and personalization. Proc. SemSearch 2008, CEUR Workshop. 2 – 13.
  27. Page, L., Brin, S., Motwani, R., & Winograd, T. (1999). The PageRank citation ranking: bringing order to the Web. Technical Report SIDL-WP-1999-0120. Stanford University.
  28. Phan, X. (2006). CRFTagger: CRF English POS Tagger, developed by Xuan-Hieu Phan, Graduate School of Information Sciences, Tohoku University. Http:// Salton, G., & Buckley, C. (1988). Term-weighting approaches in automatic text retrieval. International Journal of Information Processing and Management 24 (5), 513– 523.
  29. Strube, M., & Ponzetto, S. (2006). WikiRelate! Computing semantic relatedness using Wikipedia. Proc. National Conference on Artificial Intelligence (AAAI-06), 1419– 1424.
  30. Verbert, K., & Duval, E. (2004) Towards a global architecture for learning objects: a comparative analysis of learning object content models. Proc. World Conference on Educational Multimedia, Hypermedia and Telecommunications, 202 – 209.
  31. Wang, B., & Brookes, G. (2004). A semantic approach for Web indexing. Proc. Sixth AsiaPacific Web Conference, LNCS 3007, 59– 68.

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