1,720,970 research outputs found
Sequences of refinements of rough sets: logical and algebraic aspects
Full text linkIn this thesis, a generalization of the classical Rough set theory is developed considering the so-called sequences of orthopairs that we define as special sequences of rough sets.
Mainly, our aim is to introduce some operations between sequences of orthopairs, and to discover how to generate them starting from the operations concerning standard rough sets. Also, we prove several representation theorems representing the class of finite centered Kleene algebras with the interpolation property, and some classes of finite residuated lattices (more precisely, we consider Nelson algebras, Nelson lattices, IUML-algebras and Kleene lattice with implication) as sequences of orthopairs.
Moreover, as an application, we show that a sequence of orthopairs can be used to represent an examiner's opinion on a number of candidates applying for a job, and we show that opinions of two or more examiners can be combined using operations between sequences of orthopairs in order to get a final decision on each candidate.
Finally, we provide the original modal logic SOn with semantics based on sequences of orthopairs, and we employ it to describe the knowledge of an agent that increases over time, as new information is provided. Modal logic Son is characterized by the sequences (□1,…, □n) and (O1,…, On) of n modal operators corresponding to a sequence (t1,…, tn) of consecutive times. Furthermore, the operator □i of (□1,…, □n) represents the knowledge of an agent at time ti, and it coincides with the necessity modal operator of S5 logic. On the other hand, the main innovative aspect of modal logic SOn is the presence of the sequence (O1,…, On), since Oi establishes whether an agent is interested in knowing a given fact at time ti
Extracting Concepts From Fuzzy Relational Context Families
Full text linkFuzzy relational formal concept analysis (FRCA) mines collections of fuzzy concept lattices from fuzzy relational context families, which are special datasets made of fuzzy formal contexts and fuzzy relations between objects of different types. Mainly, FRCA consists of the following procedures: first, an initial fuzzy relational context family is transformed into a collection of fuzzy formal contexts; second, a fuzzy concept lattice is generated from each fuzzy formal context by using one of the techniques existing in the literature. The principal tools to transform a fuzzy context family into a set of fuzzy formal contexts are the so-called fuzzy scaling quantifiers, which are particular fuzzy quantifiers based on the concept of evaluative linguistic expression. FRCA can be applied whenever information needs to be extracted from multirelational datasets including vagueness, and it can be viewed as an extension of both relational concept analysis and fuzzy formal concept analysis. This article contributes to the development of fuzzy relational concept analysis by achieving the following goals. First of all, we present and study a new class of fuzzy quantifiers, called t-scaling quantifiers, to extract fuzzy concepts from fuzzy relational context families. Subsequently, we provide an algorithm to generate, given a t-scaling quantifier, a collection of fuzzy concept lattices from a special fuzzy relational context family, which is composed of a pair of fuzzy formal contexts and a fuzzy relation between their objects. After that, we introduce an ordered relation on the set of all t-scaling quantifiers, which allows us to discover a correspondence among fuzzy concept lattices deriving from different t-scaling quantifiers. Finally, we discuss how the results obtained for t-scaling quantifiers can be extended to the class of fuzzy scaling quantifies. Therefore, this analysis highlights the main differences between t-scaling and fuzzy quantifiers
Fuzzy formal concept analysis to detect DMO’s strategic patterns towards sustainability
No full textDestination Management Organisations (DMOs) are driving the sustainability transformation at territorial level. The novel adoption of Fuzzy Formal Concept Analysis to analyse a census survey (n = 109) of Italian DMOs highlights the potential of FFCA to uncover nuanced patterns of sustainability implementation that remain hidden using more conventional methods: the co-existence of operational tourism flows management and strategic efforts aimed at advancing sustainability. This represents not only a methodological innovation and a valuable path to process categorical data from survey designs, but also a novel practice-oriented insight for destination managers aiming at implementing sustainability practices
Aggregation operators on shadowed sets
No full textIn this article, we study aggregation operators on shadowed sets. In particular, since shadowed sets can be obtained as approximations of fuzzy sets, we explore the relationships between aggregation operators on fuzzy sets and corresponding operators on shadowed sets. We focus on studying conditions under which the approximations of fuzzy sets into shadowed sets represent an homomorphism with respect to the corresponding aggregation operators, and we propose classes of fuzzy set operators that correspond to (and satisfy the same properties as) specific shadowed set operators.(c) 2022 Elsevier Inc. All rights reserved
Kleene algebras as sequences of orthopairs
No full textWe study sequences of approximations of sets given by refining tolerance relations on the universe, and we show that such sequences can be equipped with a structure of finite centered Kleene algebra satisfying the interpolation property. We further show that every such Kleene algebra is isomorphic to the algebra of sequences of approximations of subsets of a suitable universe
Finite IUML-algebras, Finite Forests and Orthopairs
No full textWe show that finite IUML-algebras, which are residuated lattices arising from an idempotent uninorm, can be interpreted as algebras of sequences of orthopairs whose main operation is defined starting from the three-valued Sobociński operator between rough sets. Our main tool is the representation of finite IUML-algebras by means of finite forests
sj-docx-1-msj-10.1177_13524585231217918 – Supplemental material for Clinical and radiological correlates of apathy in multiple sclerosis
No full textSupplemental material, sj-docx-1-msj-10.1177_13524585231217918 for Clinical and radiological correlates of apathy in multiple sclerosis by Francesco Tazza, Simona Schiavi, Elisa Leveraro, Maria Cellerino, Giacomo Boffa, Stefania Ballerini, Mara Dighero, Antonio Uccelli, Elvira Sbragia, Kenda Aluan, Matilde Inglese and Caterina Lapucci in Multiple Sclerosis Journal</p
Context-aware advertisment recommendation on twitter through rough sets
No full textThe main, if not the only, income for social networks is from advertising. Social media platforms like Twitter have become a main stream communication medium to disseminate information and capture the interest of potential customers. So, it is crucial that the policy implemented to decide which ads to show in proximity of which user's posts, is the most profitable one: the ads shown should be as much as possible targeted to the user's interests. In this paper, we propose a context-aware advertising recommendation system that, analyzing the users' tweets during the timeline, interpretes the personal interests of users through orthopairs (they are equivalent to rough sets) to meet ads and users' interests at the right time
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