arXiv:2111. 15255v2 Announce Type: replace-cross Abstract: The probabilistic linguistic term has been proposed to deal with probability distributions in provided linguistic evaluations.
arXiv:2607. 23243v1 Announce Type: new Abstract: Fuzzy Integral (FI) based aggregation provides a powerful mechanism for nuanced aggregation, for example, in ensemble approaches or decision-level fusion more generally.
The paper introduces the concept of matrix aggregation operators (MAOs), a formal framework for aggregating data naturally arranged in matrices, such as membership degrees in fuzzy systems. It examines properties like decomposability and symmetry, showing that some MAOs cannot be expressed in decomposable form. The authors also propose a new family of MAOs called maximum entropy global coverage indices (MEGCIs), constructed from grouping functions and MEOWA operators, and demonstrate their effectiveness in assessing cluster quality through extensive experiments.
arXiv:2607. 10038v1 Announce Type: cross Abstract: For many years, the pairwise comparison method has been widely used for decision-making involving experts.
arXiv:2608. 05958v1 Announce Type: new Abstract: The paper addresses several ranking-dependent decision support methods.
arXiv:2609.16779v1 Announce Type: new Abstract: LLMs are increasingly employed in a wide range of decision-making tasks. However, the opacity of their internal reasoning makes it difficult to validat...
arXiv:2606. 17756v1 Announce Type: new Abstract: Fairness has become a central concern in ranking problems involving individuals or social groups, particularly under the Responsible Artificial Intelligence agenda.
arXiv:2608. 19234v1 Announce Type: new Abstract: Decision-making in complex systems often involves dealing with imprecise or uncertain information, frequently represented using fuzzy sets, particularly Triangular Fuzzy Numbers (TFNs).
arXiv:2607. 03550v1 Announce Type: new Abstract: Human reasoning often operates through qualitative concepts expressed by linguistic labels such as high, low, expensive, or cheap, whose interpretation depends on context and is usually vague, despite being rooted in numerical data.
The article addresses a specific data clustering problem: identifying groups of adjacent text segments of a suitable length that match a fuzzy pattern defined by a sequence of fuzzy properties. It proposes a heuristic algorithm that uses a prefix structure to efficiently map text segments to fuzzy properties, and proves that for the special case of unit-length segments (fuzzy string matching), the algorithm finds all matching segments. Additionally, it presents a dynamic programming approach to determine the best segmentation of an entire text based on a fuzzy pattern.
arXiv:2607. 07313v1 Announce Type: cross Abstract: Pairwise comparison (PC) via pairwise reciprocal matrices (PRMs) is central to the Analytic Hierarchy Process (AHP).
We propose a new design of fair classifiers for multi-class classification problems in the presence of vector-valued sensitive attributes. In that scenario each sensitive attribute has multiple values...
arXiv:2607. 04983v1 Announce Type: cross Abstract: This article is about the development of a fuzzy cognitive map using a local large language model.