Ordinal Measures for Image Correspondence
IEEE Transactions on Pattern Analysis and Machine Intelligence
A similarity-based generalization of fuzzy orderings preserving the classical axioms
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Representations and constructions of similarity-based fuzzy orderings
Fuzzy Sets and Systems - Special issue: Preference modelling and applications
Mining rank-correlated sets of numerical attributes
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Statistics to measure correlation for data mining applications
Computational Statistics & Data Analysis
On rank correlation in information retrieval evaluation
ACM SIGIR Forum
A new rank correlation coefficient for information retrieval
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Testing noisy numerical data for monotonic association
Information Sciences: an International Journal
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The so-called gamma coefficient is a well-known rank correlation measure frequently used to quantify the strength of dependence between two variables with ordered domains. To increase the robustness of this measure toward noise in the data, a generalization of the gamma coefficient has recently been developed on the basis of fuzzy order relations. The goal of this paper is threefold. First, we analyze some formal properties of the fuzzy gamma coefficient. Second, we complement the original experiments, which have been conducted on a simple artificial data set, by a more extensive empirical evaluation using real-world data. On the basis of these empirical results, we provide some basic insights and offer an explanation for the effectiveness of the fuzzy gamma coefficient. Third, we propose an alternative motivation for the measure, based on the idea of (fuzzy) equivalence relations induced by limited precision in the perception of measurements.