INDIVIDUALIZING USER INTERFACES - APPLICATION OF THE GRADE OF MEMBERSHIP (GOM) MODEL FOR DEVELOPMENT OF FUZZY USER CLASSES

Application of fuzzy set theory [35] provides a conceptual framework f or empirical development of fuzzy user classes for measurement of comp uter users. Fuzzy classes generalize discrete (fixed boundary) classes by assigning scores that relate each person to each class for represe nting within-class heterogeneity [13, 25]. Use of fuzzy classes permit s individual heterogeneity to be represented by a relatively few analy tically defined types [14]. Applying the properties of fuzzy set theor y to user classification will result in the definition of a user's mem bership within a series of fuzzy user classes within the user space. T hese fuzzy classes can be considered an alternative method for definin g stereotypes by empirically defining potential categories into which users can be assigned. The major difference between fuzzy user classes and stereotypes lies in the application of grades of membership to di rectly measure simultaneous membership in multiple categories. Thus, v ariability can be very accurately measured and represented using fuzzy sets and grades of membership. These fuzzy classes or user types repr esent archetypical users or fuzzy users. Application of fuzzy set theo ry provides an opportunity to extend the current classification method s to measure the differences between users more accurately. This incre ase in accuracy assists in developing effective adaptive human compute r interfaces.