Previous |  Up |  Next


usability; Choquet integral; inquiry methods
The concept of usability of man-machine interfaces is usually judged in terms of a number of aspects or attributes that are known to be subject to some rough correlations, and that are in many cases given different importance, depending on the context of use of the application. In consequence, the automation of judgment processes regarding the overall usability of concrete interfaces requires the design of aggregation operators that are capable of modeling approximate or ill-defined interactions among criteria. In addition, justified expert opinions are given a prominent status in the current practice of usability evaluation, which points to the convenience of including experts as an integral part of the aggregation operator design process. On the basis of these assumptions we review in this paper possible approaches to design a suitable aggregation operation and describe a method for such kind of design process that explicitly models expert-elicited relationships among criteria, enforcing some properties on a Choquet capacity. The method subsequently uses experimental data to fine-tune operator design. A case study is described to illustrate the method, and a comparative study with other common aggregation approaches is also provided.
[1] Beliakov G.: How to build aggregation operators from data? Internat. J. Intelligent Systems 18 (2003), 903–923 DOI 10.1002/int.10120
[2] Beliakov G., Mesiar, R., Valášková, L ’.: Fitting generated aggregation operators to empirical data. Internat. J. Uncertainty, Fuzziness and Knowledge-based Systems (2003) (to appear) MR 2075312 | Zbl 1073.28012
[3] Brajnik J.: Towards valid quality models for websites. In: Proc. 7th Human Factors and the Web Conference, 2001
[4] Calvo T., Kolesárová A., Komorníková, M., Mesiar R.: Aggregation operators: Basic concepts, issues and properties. In: Aggregation Operators: New Trends and Applications (T. Calvo, G. Mayor, and R. Mesiar, eds.), Studies in Fuzziness and Soft Computing 97 (2002), 3–106 MR 1936383
[5] Dix A., Abowd G., Beale, R., Finlay J.: Human-Computer Interaction. Prentice Hall, Englewood Cliffs, N.J. 1998 Zbl 0812.68026
[6] Frøkjær E., Hertzum, M., Hornbæk K.: Measuring usability: are effectiveness, efficiency and satisfaction really correlated? In: Proc. Human Factors in Computing Systems, 2000, pp. 345–352
[7] Grabisch M.: A new algorithm for identifying fuzzy measures and its application to pattern recognition. In: IEEE Fuzzy Systems Internat. Joint Conference 1995, pp. 145–150
[8] Grabisch M.: The application of fuzzy integrals in multicriteria decision making. European J. Oper. Res. 89 (1996), 445–456 DOI 10.1016/0377-2217(95)00176-X | Zbl 0916.90164
[9] Grabisch M.: The interaction and Mobius representations of fuzzy measures on finite spaces, $k$-additive measures: a survey. In: Fuzzy Measures and Integrals. Theory and Applications (M. Grabisch, T. Murofushi, and M. Sugeno, eds.), Physica–Verlag, Heidelberg 2000, pp. 70–93 MR 1767746
[10] Bevan N.//ISO 9241: Ergonomic requirements for office work with visual display terminals (VDTs) – Part 11: Guidance on usability: TC 159. SC 4 Technical Committee of International Organization for Standardization 1998
[11] Ivory M. Y., Hearst M. A.: The state of the art in automated usability evaluation of user interfaces. ACM Computing Surveys 33 (2001), 4, 1–47 DOI 10.1145/503112.503114
[12] Izyumov B., Kalinina, E., Wagenknecht M.: Software tools for regression analysis of fuzzy data. In: Proc. 9th Zittau Fuzzy Colloquium 2001, pp. 221–229
[13] Kalinina E., Wagenknecht M.: Fuzzy regression analysis and application to a crisp model. In: Proc. 8th Zittau Fuzzy Colloquium 2000
[14] Kirakowski J., Cierlik B.: Measuring the usability of web sites. In: Human Factors and Ergonomics Society Annual Conference 1998
[15] Klayman J., Ha Y.-W.: Confirmation, disconfirmation, and information in hypothesis testing. Psychological Review 94 (1987), 2, 211–228 DOI 10.1037/0033-295X.94.2.211
[16] Linstone H., (eds.) M. Turoff: The Delphi Method: Techniques and Applications. Addison Wesley, Reading 1975 Zbl 0347.62081
[17] Marichal J. L.: An axiomatic approach of the discrete Choquet integral as a tool to aggregate interacting criteria. IEEE Trans. Fuzzy Systems 8 (2000), 6, 800–807 DOI 10.1109/91.890347
[18] Nielsen J.: Heuristic evaluation. In: Usability Inspection Methods (J. Nielsen and R. L. Mack, eds.), Wiley, New York 1994, pp. 25–61
[19] Nielsen J.: Guerrila HCI: using discount usability engineering to penetrate the intimidation barrier. In: Cost-Justifying Usability (R. G. Bias and D. J. Mayhew, eds.), Academic Press, New York 1994, pp. 245–272
[20] Olsina L., Rossi G.: Measuring Web application quality with WebQEM. IEEE Multimedia Magazine 9 (2002), 4, 20–29 DOI 10.1109/MMUL.2002.1041945
[21] Sicilia M. A., García E.: Modelling interacting Web usability criteria through fuzzy measures. In: Proc. 3rd Internat. Conference on Web Engineering (Lecture Notes in Computer Science 2722), Springer–Verlag, Berlin 2003, pp. 182–185 Zbl 1029.68901
[22] Sicilia M. A., García, E., Calvo T.: On the use of the Choquet integral for the aggregation of usability interface related scores. In: Proc. Summer School on Aggregation Operators (AGOP 2003), University of Alcala de Henares (Spain), 2003, pp. 159–164
[23] Sicilia M. A., García, E., Alcalde R.: Fuzzy specializations and aggregation operator design in competence-based human resource selection. In: Proc. 8th World Federation on Soft Computing Conference 2003 (to appear)
[24] Welie M. Van, Veer G. C. van der, Eliëns A.: Breaking down usability. Proc. Interact’99 (1999), pp. 613–620
Partner of
EuDML logo