An explainable prediction method based on Fuzzy Rough Sets, TOPSIS and hexagons of opposition: Applications to the analysis of Information Disorder

被引：8

作者：

Gaeta, Angelo ^{[1
]}

Loia, Vincenzo ^{[1
]}

Orciuoli, Francesco ^{[1
]}

机构：

[1] Univ Salerno, Dipartimento Sci Aziendali Management & Innovat Sy, Via Giovanni Paolo II 132, I-84084 Fisciano, SA, Italy

来源：

INFORMATION SCIENCES | 2024年 / 659卷

关键词：

Fuzzy Rough Sets; Structures of opposition; TOPSIS; Information Disorder; DECISION-MAKING; NEWS;

D O I：

10.1016/j.ins.2023.120050

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页数：16

共 49 条

[1] Detecting influential news in online communities: An approach based on hexagons of opposition generated by three-way decisions and probabilistic rough sets [J].