Implementing Fuzzy Subtractive Clustering to Build a Personality Fuzzy Model Based on Big Five Patterns for Engineers

Data mining has become an essential component in various fields of human life including business, education, medical and scientific. Cluster analysis is an important data mining technique used to find data segmentation and pattern recognition. This paper proposes the application of Fuzzy Subtractive Clustering (FSC) technique as an approach to define Big Five Patterns (B5P) using psychometric tests for students in engineering programs. In comparison with an ANFIS Learning Approach, FSC gives us a better and broader relationship of the behavioral pattern between B5 traits and careers. This will help students find a better way to choose a career and relate their personality with career planning or for job advice; and school counselors as a tool to guide their students in career counseling.