DaMIM_Data

This study proposes and validates a data mining-based interface development method (DaMIM) to optimize menu-driven user interfaces. DaMIM comprises six steps—target task definition, user selection, data collection, application of data mining techniques, analysis and evaluation, and determination of alternatives. Cluster analysis is used as the data mining technique. The proposed method is validated using a program developed to measure the reaction times of menu selection. Two types of experiments are performed—name-matching experiments, in which menu names are displayed, and definition-guessing experiments, in which definitions are displayed. In addition, the experiments are classified as low density (9) or high density (14) depending on the number of menus, and alphabetical method, object-oriented method, process-oriented method, or data mining-based method (DM) are used for menu organization. The results reveal that statistically significant differences are not observed between the menu selection response times of the different menu organization methods at low density in both the name-matching and definition-guessing experiments, However, the response time of DM is the shortest in the high density case. Therefore, the effectiveness of DM is verified. The conclusions of this study are expected to contribute toward the objectification and productivity improvement of user-based interface design.