Abstract
As a decision support system, we implemented the Multi-Attribute Global Inference of Quality (MAGIQ) method in patent applications. By employing the Rank Order Centroid (ROC) weighting approach, we determined that MAGIQ provides an effective and efficient solution for addressing challenges in the patent application process. Although previous studies have applied MAGIQ to software quality evaluation, our application in selecting patent applicants introduces a new perspective. Our analysis identified Applicant 2 as the most suitable, achieving the highest score of 0.454861. Furthermore, when comparing our results with those derived from the Analytical Hierarchy Process (AHP) method, we observed a high consistency in rankings, affirming MAGIQ's reliability. Consequently, we suggest applying MAGIQ to more intricate problems to delve deeper into its potential and constraints in diverse contexts
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