Skip to main content
SpringerLink
Log in

Using consensus methods to construct adaptive interfaces in multimodal web-based systems

  • Long paper
  • Published:
Universal Access in the Information Society Aims and scope Submit manuscript

Abstract

This paper presents a concept of adaptive development of user interfaces in multimodal web-based systems. Today, it is crucial for general access web-based systems that the user interface is properly designed and adjusted to user needs and capabilities. It is believed that adaptive interfaces could offer a possible solution to this problem. Here, we introduce the notion of the user profile for classification, the interface profile for describing the system interface, and the compound usability measure for evaluation of the interface. Consensus-based methods are applied for constructing the interface profiles appropriate to classes of users.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Arafa Y, Mamdani A (2000) Virtual personal service assistants: towards real-time characters with artificial hearts. In: Proc intelligent user interfaces. New Orleans, LA USA, pp 9–12

  2. Barthelemy JP (1988) Thresholded consensus for n-trees. J Classif 5:229–236

    Google Scholar 

  3. Bogart KP (1973) Preference structure I: distance between transitive preference relations. J Math Sociol 3:455–470

    Google Scholar 

  4. Breese J, Heckermen D, Kadie C (1998) Empirical analysis of predictive algorithms for collaborative filtering. Technical report, Microsoft Research, October

  5. Brown SM, Santos E, Banks SB, Oxley ME (1998) Using explicit requirements and metrics for interface agent user model for interface agent user model correction. In: Proc 2nd Int Conf Autonomous Agents, Minneapolis, Minnesota, USA, pp 1–7

  6. Dattola RT (1968) A fast algorithm for automatic classification. Report ISR-14 to the National Science Foundation, Section V, Cornell University, Department of Computer Science

  7. Day WHE (1988) Consensus methods as tools for data analysis. In: Bock HH (ed) Classification and related Methods of Data Analysis. Proc IFCS’87, North-Holland, pp 317–324

  8. Estivil-Castro V, Yang J (2001) Categorizing visitors dynamically by fast and robust clustering of access logs. In: LNAI 2198. Springer, Berlin Heidelberg New York, pp 498–507

  9. Expression of Interest (2002) Thematic Priorities. FP6. http://www.cordis.lu/fp6/eoi-instuments/infosoc.htm

  10. Fleming M, Cohen R (1999) User modelling in the design of interactive interface agents. In: Proc 7th Int Conf User Modeling, pp 67–76

  11. Hackos JT, Redish JD (1998) User and Task Analysis for Interface Design. Appendix C. John Wiley and Sons, New York, pp 457–478

  12. Hedberg SR (1998) Is AI going mainstream at last? A look inside Microsoft Research. IEEE Intell Syst 3/4:21–25

    Google Scholar 

  13. International Standard ISO 9241-10 (1996) Ergonomic requirements for office work with visual display terminals (VDTs) – Part 10: Dialogue principles

  14. International Standard ISO 9241-11 (1997) Ergonomic requirements for office work with visual display terminals (VDT’s) – Part 11: Guidance on Usability

  15. Keeble RJ, Macredie RD, Williams DS (2000) User environments and individuals: experience with adaptive agents. Cognition Technol Work 2:16–26

    Google Scholar 

  16. Kobsa A, Koenemann J, Pohl W (2001) Personalized hypermedia presentation techniques for improving online customer relationships. Knowl Eng Rev 16(2):111–155

    Google Scholar 

  17. Lieberman H (1997) Autonomous interface agents. Proc CHI 97, ACM, pp 67–74

  18. Maglio PP, Barrett R, Campbell CS, Selker T (2000) SUITOR: an attentive information system. In: Proc 2000 Int Conf Intelligent User Interfaces, pp 169–176

  19. McMorris FR, Mulder HM, Powers RC (2000) The median function on median graphs and semilattices. Discrete Appl Math 101:221–230

    Google Scholar 

  20. McMorris FR, Powers RC (1995) The median procedure in a formal theory of consensus. SIAM J Discrete Math 14:507–516

    Google Scholar 

  21. Mobasher B, Cooley R, Srivastava J (2000) Automatic personalization based on Web usage mining. Commun ACM 8(43):142–151

    Google Scholar 

  22. Nasraoui O, Frigui H, Joshi A, Krishnapuram R (1999) Mining Web access logs using relational competitive fuzzy clustering. In: Proc 8th Int Fuzzy Systems Association World Congr, August 1999, pp 28–36

  23. Newman WM, Lamming MG (1996) Interactive System Design. Addison-Wesley, Harlow

  24. Nguyen NT (2001) Consensus-based timestamps in distributed temporal databases. Comput J 44(5):398–409

    Google Scholar 

  25. Nguyen NT (2000) Using consensus methods for solving conflicts of data in distributed systems. In: LNCS. vol 1963, pp 409–417

  26. Nguyen NT (2001) Using distance functions to solving representation choice problem. Fundamenta Informaticae 48(4):295–314

    Google Scholar 

  27. Peerce J, Rogers Y, Benyon D, Holland S, Carem T (1996) Human-Computer Interaction. Addison-Wesley, Harlow

  28. Quinn LM, Pawasarat J (2001) Confronting anti-urban marketing stereotypes: a Milwaukee economic development challenge. June 2001. http://www.uwm.edu/Dept/ETI/purchasing/markets.htm

  29. Rijsbergen C v (1979) Information Retrieval. 2nd edn. Butterworths, London

  30. Schneiderman B, Maes P (1997) Debate: direct manipulation vs. interface agents. Interactions 4(6):42–61

    Google Scholar 

  31. Shneiderman B (2000) Universal usability. Commun ACM 43(5):85–91

    Google Scholar 

  32. Shearin S, Lieberman H (2001) Intelligent profiling by example. In: Proc Conf Intelligent User Interfaces, ACM Press, 2001

  33. Sobecki J, Nguyen NT (2001) Consensus-based adaptive user interface for universal access systems. In: Stephanidis C (ed) Proc 9th Int Conf Human-Computer Interaction and 1st Int Conf Universal Access in Human-Computer Interaction. LEA, London, vol 3: pp 112–116

  34. Sobecki J (2001) One suits all – is it possible to build a single interface appropriate for all users? In: Grzech A, Wilimowska Z (eds) Proc 23rd Int Scientific School ISAT, PWr Press, Wroclaw, pp 125–131

  35. Spolsky J (2001) User interface design for programmers. Apress LP

  36. Stary C (2001) User diversity and design representation: towards increased effectiveness in Design for All. Int J UAIS 1:16–30

    Google Scholar 

  37. Stephanidis C, Savidis A (2001) Universal Access in the Information Society: methods, tools, and interaction technologies. Int J UAIS 1:40–55

    Google Scholar 

  38. Whalen D (2002) The Unofficial Cookie FAQ, Version 2.54. Contributed to Cookie Central by David Whalen. http://www.cookiecentral.com/faq/#2.7

  39. Wooldridge M, Jennings NR (1995) Intelligent agents: theory and practice. Knowl Eng Rev 100(2):115–152

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Information Systems, Wroclaw University of Technology, Wyb. St. Wyspianskiego 27, 50-370, Wroclaw, Poland

    Ngoc Thanh Nguyen & Janusz Sobecki

Authors
  1. Ngoc Thanh Nguyen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Janusz Sobecki
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Ngoc Thanh Nguyen or Janusz Sobecki.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Nguyen, N., Sobecki, J. Using consensus methods to construct adaptive interfaces in multimodal web-based systems. UAIS 2, 342–358 (2003). https://doi.org/10.1007/s10209-003-0050-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10209-003-0050-1

Keywords

Search

Navigation