Cognitive Diversity: A Measurement of Dissimilarity Between Multiple Scoring Systems

Abstract

In the context of computing and informatics, Cognitive Diversity (CD) has been proposed to characterize the degree of dissimilarity between multiple scoring systems (MSS). As such, CD serves a role in informatics analogous to that of Pearson’s Correlation in classical statistics. Here we review MSS and explore CD’s utility in relation to the notions of correlation and distance in machine learning, ensemble methods, rank aggregation, and combinatorial fusion in both parametric score space and non-parametric rank space. Finally, we survey applications of CD in combining MSS in a variety of domains in science, technology, society, business, and management. Our study provides a new data science framework for discovery in data-rich environments.