Towards the dissolution of the sorites paradox

Trillas, Enric; Urtubey, Luis Adrian

doi:10.1016/j.asoc.2008.01.008

Cited by 10 publications

(3 citation statements)

References 5 publications

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“…Lotfi Zadeh introduced soft computing as a “collection of methodologies that aim to exploit the tolerance for imprecision and uncertainty to achieve tractability, robustness and low solution cost” (Trillas and Urtubey, 2011). Its principal constituents are fizzy logic, neurocomputing and probabilistic reasoning (PR) (Zadeh, 1994, p. 48).…”

Section: Overview Of Soft Computingmentioning

confidence: 99%

Soft computing in business: exploring current research and outlining future research directions

Singh

Koohang

et al. 2023

IMDS

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PurposeThe primary aim of this study is to detail the use of soft computing techniques in business and management research. Its objectives are as follows: to conduct a comprehensive scientometric analysis of publications in the field of soft computing, to explore the evolution of keywords, to identify key research themes and latent topics and to map the intellectual structure of soft computing in the business literature.Design/methodology/approachThis research offers a comprehensive overview of the field by synthesising 43 years (1980–2022) of soft computing research from the Scopus database. It employs descriptive analysis, topic modelling (TM) and scientometric analysis.FindingsThis study's co-citation analysis identifies three primary categories of research in the field: the components, the techniques and the benefits of soft computing. Additionally, this study identifies 16 key study themes in the soft computing literature using TM, including decision-making under uncertainty, multi-criteria decision-making (MCDM), the application of deep learning in object detection and fault diagnosis, circular economy and sustainable development and a few others.Practical implicationsThis analysis offers a valuable understanding of soft computing for researchers and industry experts and highlights potential areas for future research.Originality/valueThis study uses scientific mapping and performance indicators to analyse a large corpus of 4,512 articles in the field of soft computing. It makes significant contributions to the intellectual and conceptual framework of soft computing research by providing a comprehensive overview of the literature on soft computing literature covering a period of four decades and identifying significant trends and topics to direct future research.

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Section: Overview Of Soft Computingmentioning

confidence: 99%

Soft computing in business: exploring current research and outlining future research directions

Singh

Koohang

et al. 2023

IMDS

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“…This is why the Specification Axiom is not always valid with predicates in the same manner as in language. Ordinary, everyday, or natural language is charged with many linguistic terms, which, as shown by the Sorites methodology [3,4] when acting in a crisp set X, lack the specification of a crisp subset, but they may be specified by means of fuzzy sets [5]. Indeed, this study aims to answer the question: "what does it mean to "specify" a non-crisp predicate?"…”

Section: Introductionmentioning

confidence: 99%

A naïve way of looking at fuzzy sets

Trillas

Termini

Moraga

2016

Fuzzy Sets and Systems

Self Cite

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“…In addition, we disagree with the assumption that linguistic vagueness is only an epistemological issue that can be addressed searching for a crisp definition with enough information and time; in our opinion, vagueness is an ontological feature and should be analysed using different tools. A good example that illustrates the complexity of vague predicates is the Sorites paradox [35]. Let us suppose that a person 185cm height is tall.…”

Section: Introductionmentioning

confidence: 99%

On modeling vagueness and uncertainty in data-to-text systems through fuzzy sets

Ramos-Soto,

Pereira-Fariña

2017

Preprint

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Vagueness and uncertainty management is counted among one of the challenges that remain unresolved in systems that generate texts from non-linguistic data, known as data-to-text systems. In the last decade, work in fuzzy linguistic summarization and description of data has raised the interest of using fuzzy sets to model and manage the imprecision of human language in data-to-text systems. However, despite some research in this direction, there has not been an actual clear discussion and justification on how fuzzy sets can contribute to data-to-text for modeling vagueness and uncertainty in words and expressions. This paper intends to bridge this gap by answering the following questions:What does vagueness mean in fuzzy sets theory? What does vagueness mean in data-to-text contexts? In what ways can fuzzy sets theory contribute to improve data-to-text systems? What are the challenges that researchers from both disciplines need to address for a successful integration of fuzzy sets into datato-text systems? In what cases should the use of fuzzy sets be avoided in D2T?For this, we review and discuss the state of the art of vagueness modeling in

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Towards the dissolution of the sorites paradox

Cited by 10 publications

References 5 publications

Soft computing in business: exploring current research and outlining future research directions

Soft computing in business: exploring current research and outlining future research directions

A naïve way of looking at fuzzy sets

On modeling vagueness and uncertainty in data-to-text systems through fuzzy sets

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