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Previous issue date: 2017-01-27 / Este trabalho prop?e formula??es para o Problema de Clustering Heterog?neo Fuzzy,
assim como um m?todo heur?stico de Busca em Vizinhan?a Vari?vel para resolv?-lo. O
Problema de Clustering Heterog?neo Fuzzy ? um problema de agrupamento de dados
modelado em dois n?veis. O primeiro identifica grupos de indiv?duos cujas percep??es
acerca dos objetos envolvidos sejam similares. O segundo n?vel identifica parti??es fuzzy
de objetos para cada grupo de indiv?duos. O segundo n?vel ? baseado no problema das
p-medianas, cujo objetivo ? particionar um conjunto de objetos em subconjuntos menores
e definir um objeto para cada subconjunto como mediana, de modo que a soma das dissimilaridades
entre cada objeto e sua mediana seja m?nima. O Problema de Clustering Heterog?neo
Fuzzy generaliza o problema das p-medianas para ambientes fuzzy, permitindo
que os n?veis de pertin?ncia de cada objeto em rela??o a cada cluster sejam fracion?rios.
Essa generaliza??o permite novas interpreta??es dos resultados, como a identifica??o de
rela??es simult?neas de objetos com diferentes clusters. / This work proposes formulations for the Fuzzy Heterogeneous Clustering Problem,
as well as a heuristic method of Variable Neighborhood Search to solve it. The Fuzzy Heterogeneous
Clustering Problem is a clustering problem that is formulated in two levels.
The first identifies groups of individuals whose perceptions about the objects involved are
similar. The second level identifies fuzzy partitions of objects for each group of individuals.
The second level is based on the p-median problem, whose objective is to partition a
set of objects into smaller subsets and to define an object as median for each subset, such
that the sum of dissimilarities between each object and its median is minimal. The Fuzzy
Heterogeneous Clustering Problem generalizes the p-median problem to fuzzy environments,
allowing the degrees of membership between each object and each cluster to be
fractionary. This generalization allows new interpretations about the results, such as the
identification of simultaneous relationships of objects with different clusters.
Identifer | oai:union.ndltd.org:IBICT/oai:repositorio.ufrn.br:123456789/22566 |
Date | 27 January 2017 |
Creators | Pinheiro, Daniel Nobre |
Contributors | 03553729406, http://lattes.cnpq.br/5093210888872414, Fernandes, Eraldo Luis Rezende, 89548710110, http://lattes.cnpq.br/5878235526936399, Santi, Everton, 01310830070, http://lattes.cnpq.br/1704949855287036, Aloise, Daniel |
Publisher | PROGRAMA DE P?S-GRADUA??O EM ENGENHARIA EL?TRICA E DE COMPUTA??O, UFRN, Brasil |
Source Sets | IBICT Brazilian ETDs |
Language | Portuguese |
Detected Language | English |
Type | info:eu-repo/semantics/publishedVersion, info:eu-repo/semantics/masterThesis |
Source | reponame:Repositório Institucional da UFRN, instname:Universidade Federal do Rio Grande do Norte, instacron:UFRN |
Rights | info:eu-repo/semantics/openAccess |
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