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Modeling Users for Adaptive Semantics Visualizations

  • Kawa Nazemi
  • Dirk Burkhardt
  • Matthias Breyer
  • Arjan Kuijper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6766)

Abstract

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.

Keywords

Adaptive Visualization Semantic Visualization User Model 

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References

  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

  • Kawa Nazemi
    • 1
  • Dirk Burkhardt
    • 1
  • Matthias Breyer
    • 1
  • Arjan Kuijper
    • 1
  1. 1.Fraunhofer Institute for Computer Graphics ResearchDarmstadtGermany

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