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Conceptual conectivity analysis by means of fuzzy partitions

  • LAAS CNRS
  • CSIC - Centre of Advanced Studies of Blanes
  • Polytechnic University of Catalonia

Research output: Chapter in Book/Conference proceedingConference proceedingpeer-review

1 Citation (Scopus)

Abstract

In this paper we present a set of tools to analyze concepts that describe and explain a set of observations. Due to the inherent vagueness of concepts, that makes hard to decide in a dichotomic base weather an observation is, or is not, a good example for a concept, we consider the concepts associated to fuzzy subsets. Then we study the adequation and coverage of a collection of fuzzy sets to describe a set of observations. In the same way, once a set of concepts has been acepted to describe a set of objects, we study how the concepts are related by means of the observations, and reciprocally, how the objects are related by the concepts. Finally, a short description of the computer program COCOA is given.

Original languageEnglish
Title of host publicationUncertainty in Knowledge Bases - 3rd International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 1990
EditorsRonald R. Yager, Lotfi A. Zadeh, Bernadette Bouchon-Meunier
PublisherSpringer Verlag
Pages165-172
Number of pages8
ISBN (Print)9783540543466
DOIs
Publication statusPublished - 1991
Externally publishedYes
Event3rd International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 1990 - Paris, France
Duration: 2 Jul 19906 Jul 1990

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume521 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 1990
Country/TerritoryFrance
CityParis
Period2/07/906/07/90

Keywords

  • Classifications
  • Data analysis
  • Fuzzy sets
  • Machine learning

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