Abstract
Group-ranking problems are widely encountered decision problems which combine personal preferences to form an integrated group priority; however, providing support to solve group-ranking problems is difficult because each person has his/her own viewpoint regarding how such decisions should be made. In addition, many researchers have shown that visual aids are useful in helping users comprehend decision backgrounds. Therefore, determining how to support the group-ranking process and providing visual aids is an important issue. This study proposes a novel graphical approach to discover group consensus sequences. First, a counting-based data mining approach is constructed to discover a consensus preference matrix. Second, an ordinal Gower plot can be drawn whereby group consensus sequences can be directly observed. Unlike previous methods, the proposed approach can discover group consensus sequences without involving tedious candidate generation and exhaustive search processes, derive a total ranking list, as well as provide visual aids to users.
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