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Fuzzy Natural Logic in IFSA-EUSFLAT 2021

Fuzzy Natural Logic in IFSA-EUSFLAT 2021

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The present book contains five papers accepted and published in the Special Issue, “Fuzzy Natural Logic in IFSA-EUSFLAT 2021”, of the journal Mathematics (MDPI). These papers are extended versions of the contributions presented in the conference “The 19th World Congress of the International Fuzzy Systems Association and the 12th Conference of the European Society for Fuzzy Logic and Technology jointly with the AGOP, IJCRS, and FQAS conferences”, which took place in Bratislava (Slovakia) from September 19 to September 24, 2021. Fuzzy Natural Logic (FNL) is a system of mathematical fuzzy logic theories that enables us to model natural language terms and rules while accounting for their inherent vagueness and allows us to reason and argue using the tools developed in them. FNL includes, among others, the theory of evaluative linguistic expressions (e.g., small, very large, etc.), the theory of fuzzy and intermediate quantifiers (e.g., most, few, many, etc.), and the theory of fuzzy/linguistic IF–THEN rules and logical inference. The papers in this Special Issue use the various aspects and concepts of FNL mentioned above and apply them to a wide range of problems both theoretically and practically oriented. This book will be of interest for researchers working in the areas of fuzzy logic, applied linguistics, generalized quantifiers, and their applications.

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Keywords

  • auction fraud
  • closeness
  • closeness matrix
  • closeness space
  • evaluative expressions
  • evolving fuzzy neural network
  • function similarity
  • fuzzy grammar
  • fuzzy intermediate quantifiers
  • fuzzy partition
  • fuzzy Peterson’s syllogisms
  • fuzzy transform
  • graded Peterson’s cube of opposition
  • grammaticality
  • knowledge extraction
  • linguistic complexity
  • linguistic constraints
  • linguistic gradience
  • linguistic universals
  • Mathematics & science
  • n/a
  • or-neuron
  • preimage problem
  • Reference, information & interdisciplinary subjects
  • Research & information: general
  • sentiment analysis
  • singular value decomposition

Links

DOI: 10.3390/books978-3-0365-6148-6

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