(An) interactive idea categorizer for group decision support system

Abstract

Important matters in an organizations are decided by a group which consists of numerous specialists rather than an individual. Researches on group decisions and group decision support systems have been increased rapidly over the past few years. One of the important research field in GDSS, is on effectiveness of GDSSs. Research on effectiveness according to the various cultural diversity is considered necessary to develop an appropriate GDSS for its own cultural context. Although various issues were raised in empirical research using an existing GDSS, we try to solve an issue on idea categorizing in this study. Idea categorizing in an existing GDSS was performed in a top-down procedure and mostly by participants manual works. This resulted in long idea categorizing time as much as idea generating time, clustering an idea in multiple categories, and identifying almost redundant categories. To solve these problem, we suggest an interactive idea categorizing method which a bottom-up approach. This method consists of step presenting idea using keywords, identifying keyword``s affinity, computing similarity among ideas, and clustering ideas. This method allows iterative interaction to participants for clear manifestation of ambiguous ideas. We also develop an prototype interactive idea categorizer(IIC) to test this bottom-up approach.