An explainable prediction method based on Fuzzy Rough Sets, TOPSIS and hexagons of opposition: Applications to the analysis of Information Disorder
Angelo Gaeta, Vincenzo Loia, Francesco Orciuoli
Abstract
This paper presents a novel approach for predicting and explaining instances of Information Disorder. The paper reports two significant findings: i) the use of structures of opposition to describe relationships between instances of Information Disorder, and ii) the development of an explainable prediction method that combines Fuzzy Rough Sets and TOPSIS with these structures. The findings have the potential to assist analysts and decision-makers in gaining a deeper understanding of the phenomenon of Information Disorder. The results are based on real data and demonstrate promising applications for future research.
Topics & Concepts
Opposition (politics)Computer scienceRough setData miningTOPSISFuzzy logicPhenomenonArtificial intelligenceMachine learningOperations researchMathematicsEpistemologyPolitical sciencePoliticsPhilosophyLawRough Sets and Fuzzy LogicEEG and Brain-Computer InterfacesCurrency Recognition and Detection