24 research outputs found
Concept lattices associated with L-Fuzzy W-contexts
\begin{abstract}
\noindent We generalize in this paper the
-Fuzzy concept theory we developed in a previous paper ([1]),
using the composition of -Fuzzy relations. This theory models knowledge
acquisition and
classification and takes as departure point Wille's idea ([5]).
We begin the work defining -Fuzzy W-contexts as the tuples (L,W,X,Y,
) where W, X and Y are the sets of labels, objects and
attributes respectively, and
is an -Fuzzy relation.
From these contexts, we will give the operators needed to define the \linebreak
-Fuzzy W-concepts.
These concepts will be pairs of relations () where ,
satisfying and with the operator 1 and 2 definitions given.
After proving the lattice structure of the -Fuzzy W-concepts set, we
analyse a practical
example where we interpret the new concept definition
\bigskip
\noindent {\bf Key words:}
-Fuzzy concepts, -Fuzzy W-concepts,
-Fuzzy W-contexts, Conceptual knowledge.
\end{abstract
The use of two relations in L-fuzzy contexts
In the analysis of relations among the elements of two sets it is usual to obtain different values depending on the point of view from which these relations are measured. The main goal of the paper is the modelization of these situations by means of a generalization of the L-fuzzy concept analysis called L-fuzzy bicontext. We study the L-fuzzy concepts of these L-fuzzy bicontexts obtaining some interesting results. Specifically, we will be able to classify the biconcepts of the L-fuzzy bicontext. Finally, a practical case is developed using this new tool.This work has been partially supported by the Research Group “Intelligent
Systems and Energy (SI+E)” of the Basque Government, under
Grant IT677-13, by the Research Groups “Artificial Intelligence and Approximate
Reasoning” and “Adquisición de conocimiento y minería de datos,
funciones especiales y métodos numéricos avanzados” of the Public University
of Navarra and by project TIN2013-40765-P