Modeling Users for Adaptive Semantics Visualizations

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6766)


The automatic adaptation of information visualization systems to the requirements of users plays a key-role in today’s research. Different approaches from both disciplines try to face this phenomenon. The modeling of user is an essential part of a user-centered adaptation of visualization. In this paper we introduce a new approach for modeling users especially for semantic visualization systems. The approach consists of a three dimensional model, where semantic data, user and visualization are set in relation in different abstraction layer.


Adaptive Visualization Semantic Visualization User Model 


  1. 1.
    Ahn, J.-w., Brusilovsky, P.: Adaptive visualization of search results: Bringing user models to visual analytics. Information Visualization  8/3, 167–179 (2009)CrossRefGoogle Scholar
  2. 2.
    Anderson, J.R., Lebiere, C.: Atomic Components of Thought. Lawrence Erlbaum Associates, Hillsdale (1998)Google Scholar
  3. 3.
    Ardissono, L., Console, L., Torre, I.: An adaptive system for the personalised access to news. AI Communications 14, 129–147 (2001)zbMATHGoogle Scholar
  4. 4.
    Arens, Y., Hovy, E.: The design of a model-based multimedia interaction manager. Artif. Intell. Rev.  9(2-3), 167–188 (1995)Google Scholar
  5. 5.
    Beaumont, I.: User modeling in the interactive anatomy tutoring system ANATOMTUTOR. User Modeling and User-Adapted Interaction 4(1), 21–45 (1994)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Boyle, C., Encarnacion, A.O.: MetaDoc: an adaptive hypertext reading system. User Modeling and User-Adapted Interaction 4(1), 1–19 (1994)CrossRefGoogle Scholar
  7. 7.
    Brailsford, T.J., Stewart, C.D., Zakaria, M.R., Moore, A.: Autonavigation, links, and narrative in an adaptive Web-based integrated learning environment. In: Proc. of The 11th International World Wide Web Conference (2002)Google Scholar
  8. 8.
    Brusilovsky, P., Mill, E.: User models for adaptive hypermedia and adaptive educational systems. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) Adaptive Web 2007. LNCS, vol. 4321, pp. 3–53. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  9. 9.
    Encarnação, L.M.: Multi-level user support through adaptive hypermedia: A highly application-independent help component. In: Moore, J., Edmonds, E., Puerta, A. (eds.) Proc. of 1997 International Conference on Intelligent User Interfaces, pp. 187–194. ACM, New York (1997)Google Scholar
  10. 10.
    Fischer, G.: User modeling in human-computer interaction. User Modeling and User Adapted Interaction 11(1-2), 65–86 (2001)CrossRefzbMATHGoogle Scholar
  11. 11.
    Goldstein, I.P.: The genetic graph: a representation for the evolution of procedural knowledge. In: Sleeman, D.H., Brown, J.S. (eds.) Intelligent Tutoring Systems, pp. 51–77. Academic Press, London (1982)Google Scholar
  12. 12.
    Goodman, B.A., Litman, D.J.: On the interaction between plan recognition and intelligent interfaces. User Modeling and User-Adapted Interaction 2(1), 83–115 (1992)CrossRefGoogle Scholar
  13. 13.
    Gotz, D., Wen, Z.: Behavior-driven visualization recommendation. In: Gotz, D., Wen, Z. (eds.) IUI 2009: Proceedings of the 13th International Conference on Intelligent User Interfaces, pp. 315–324. ACM, New York (2009)Google Scholar
  14. 14.
    Kao, T.-H., Yuan, S.-M.: Designing an XML-based context-aware transformation framework for mobile execution environments using CC/PP and XSLT. Computer Standards & Interfaces 26(5), 377–399 (2004)CrossRefGoogle Scholar
  15. 15.
    Kawai, K., Mizoguchi, R., Kakusho, O., Toyoda, J.: A framework for ICAI systems based on inductive inference and logic programming. New Generation Computing 5, 115–129 (1987)CrossRefGoogle Scholar
  16. 16.
    Keim, D., Andrienko, G., Fekete, J.-D., et al.: Visual Analytics: Definition, Process, and Challenges. In: Kerren, A., Stasko, J., Fekete, J.-D., et al. (eds.) Information Visualization (Lecture Notes in Computer Science, pp. 154–175. Springer, Heidelberg (2008)Google Scholar
  17. 17.
    Keim, D.A., Mansmann, F., Schneidewind, J., Thomas, J., Ziegler, H.: Visual analytics: Scope and challenges. In: Simoff, S.J., Böhlen, M.H., Mazeika, A. (eds.) Visual Data Mining. LNCS, vol. 4404, pp. 76–90. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  18. 18.
    López, J.M., Millán, E., Pérez-de-la-Cruz, J.-L., Triguero, F.: ILESA: a Web-based Intelligent Learning Environment for the Simplex Algorithm. In: Alvegård, C. (ed.) Proc. of CALISCE 1998, 4th International Conference on Computer Aided Learning and Instruction in Science and Engineering, pp. 399–406 (1998)Google Scholar
  19. 19.
    Nazemi, K., Breyer, M., Burkhardt, D., Fellner, D.W.: Visualization Cockpit: Orchestration of Multiple Visualizations for Knowledge-Exploration. International Journal of Advanced Corporate Learning 3(4), 26–34 (2010)Google Scholar
  20. 20.
    Nazemi, K., Burkhardt, D., Breyer, M., Stab, S., Fellner, D.W.: Semantic Visualization Cockpit - Adaptable Composition of Semantics-Visualization Techniques for Knowledge-Exploration. In: Proc. 13th International Conference ICL on Interactive Computer Aided Learning, ICL 2010, Hasselt, Belgium (2010) (to appear)Google Scholar
  21. 21.
    Nazemi, K., Bhatti, N., Godehardt, E., Hornung, C.: Adaptive Tutoring in Virtual Learning Worlds. In: Proceedings. CD-ROM: World Conference on Educational Multimedia, Hypermedia & Telecommunications, ED-Media 2007, Vancouver, Canada, pp. 2951–2959 (2007)Google Scholar
  22. 22.
    Nazemi, K., Stab, C., Fellner, D.W.: Interaction Analysis for Adaptive User Interfaces. In: Huang, D.-S., Zhao, Z., Bevilacqua, V., Figueroa, J.C. (eds.) ICIC 2010. LNCS, vol. 6215, pp. 362–371. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  23. 23.
    Nazemi, K., Stab, C., Fellner, D.W.: Interaction Analysis: An Algorithm for Activity and Prediction Recognition. In: Proc. 2nd IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2010. IEEE, Los Alamitos (2010) (to appear)Google Scholar
  24. 24.
    Oberlander, J., O’Donell, M., Mellish, C., Knott, A.: Conversation in the museum: experiments in dynamic hypermedia with the intelligent labeling explorer. The New Review of Multimedia and Hypermedia 4, 11–32 (1998)CrossRefGoogle Scholar
  25. 25.
    Ohlsson, S.: Constraint-based student modeling. Journal of Artificial Intelligence in Education 3(4), 429–447 (1992)Google Scholar
  26. 26.
    Pazzani, M.J., Billsus, D.: Content-based recommendation systems. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) Adaptive Web 2007. LNCS, vol. 4321, pp. 325–341. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  27. 27.
    Schafer, J.B., Frankowski, D., Herlocker, J., Sen, S.: Collaborative filtering recommender systems. In: Brusilovsky, P., Kobsa, A., Neidl, W. (eds.) Adaptive Web 2007. LNCS, vol. 4321, pp. 291–324. Springer, Heidelberg (2007)Google Scholar
  28. 28.
    Sleemann, D.H.: UMFE: a user modeling front end system. International Journal on the Man-Machine Studies 23, 71–88 (1985)CrossRefGoogle Scholar
  29. 29.
    Tarpin-Bernard, F., Habieb-Mammar, H.: Modeling elementary cognitive abilities for adaptive hypermedia presentation. User Modeling and User Adapted Interaction 15(5), 459–495 (2005)CrossRefGoogle Scholar
  30. 30.
    Thomas, J.: Visual Analytics: a Grand Challenge in Science – Turning Information Overload into the Opportunity of the Decade. In: Keynote talk IEEE InfoVis 2005, Minneapolis (2005)Google Scholar
  31. 31.
    Tsiriga, V., Virvou, M.: Modelling the Student to Individualise Tutoring in a Web-Based ICALL. International Journal of Continuing Engineering Education and Lifelong Learning 13 (3-4), 350–365 (2003)CrossRefGoogle Scholar
  32. 32.
    Wang Baldonado, M.Q., Woodruff, A., Kuchinsky, A.: Guidelines for using multiple views in information visualization. In: Proceedings of the Working Conference on Advanced Visual Interfaces, AVI 2000, Palermo, Italy, pp. 110–119. ACM, New York (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.Fraunhofer Institute for Computer Graphics ResearchDarmstadtGermany

Personalised recommendations