Reinterpreting Interpretability for Fuzzy Linguistic Descriptions of Data

Alejandro Ramos-Soto, Martín Pereira-Fariña

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

3 Citations (Scopus)
9 Downloads (Pure)

Abstract

We approach the problem of interpretability for fuzzy linguistic descriptions of data from a natural language generation perspective. For this, first we review the current state of linguistic descriptions of data and their use contexts as a standalone tool and as part of a natural language generation system. Then, we discuss the standard approach to interpretability for linguistic descriptions and introduce our complementary proposal, which describes the elements from linguistic descriptions of data that can influence and improve the interpretability of automatically generated texts (such as fuzzy properties, quantifiers, and truth degrees), when linguistic descriptions are used to determine relevant content within a text generation system.
Original languageEnglish
Title of host publicationInformation Processing and Management of Uncertainty in Knowledge-Based Systems
Subtitle of host publicationTheory and Foundations. IPMU 2018
EditorsJ Medina, M Ojeda-Aciego, J L Verdegay, J L Pelta, I P Cabrera, B Bouchon-Meunier, R R Yager
Place of PublicationCham
PublisherSpringer
Pages40-51
Number of pages12
ISBN (Electronic)978-3-319-91473-2
ISBN (Print)978-3-319-91472-5
DOIs
Publication statusPublished - 2018
Event17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems - Cádiz, Spain
Duration: 11 Jun 201815 Jun 2018
Conference number: 17
http://ipmu2018.uca.es/

Publication series

NameCommunications in Computer and Information Science
PublisherSpringer
Number853
ISSN (Print)1865-0929

Conference

Conference17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems
Abbreviated titleIPMU 2018
Country/TerritorySpain
CityCádiz
Period11/06/1815/06/18
Internet address

Keywords

  • fuzzy sets
  • linguistic summarization
  • fuzzy linguistic descriptions of data
  • interpretability
  • natural language generation
  • data-to-text

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