DUGiDocsA Homogeneous Set-Theoretical Frame for Clustering Fuzzy Relational Data
dc.contributor.author
dc.date.accessioned
2010-09-29T10:22:50Z
dc.date.available
2010-08-10T09:04:40Z
2010-09-29T10:22:50Z
dc.date.issued
2007-08
dc.identifier.citation
Clara, N. (2007). A Homogeneous Set-Theoretical Frame for Clustering Fuzzy Relational Data. Fourth International Conference on Fuzzy Systems and Knowledge Discovery : 2007 : FSKD 2007, 1, 712 - 716. Recuperat 28 setembre 2010, a http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4406016
dc.identifier.isbn
978-0-7695-2874-8
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dc.description.abstract
Our purpose is to provide a set-theoretical frame to clustering fuzzy relational data basically based on cardinality of the fuzzy subsets that represent objects and their complementaries, without applying any crisp property. From this perspective we define a family of fuzzy similarity indexes which includes a set of fuzzy indexes introduced by Tolias et al, and we analyze under which conditions it is defined a fuzzy proximity relation. Following an original idea due to S. Miyamoto we evaluate the similarity between objects and features by means the same mathematical procedure. Joining these concepts and methods we establish an algorithm to clustering fuzzy relational data. Finally, we present an example to make clear all the process
dc.format.mimetype
application/pdf
dc.language.iso
eng
dc.publisher
IEEE
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Reproducció digital del document publicat a: http://dx.doi.org/10.1109/FSKD.2007.44
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© Fourth International Conference on Fuzzy Systems and Knowledge Discovery : 2007 : FSKD 2007, 2007, vol. 1, p. 712-716
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Articles publicats (D-IMA)
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Tots els drets reservats
dc.title
A Homogeneous Set-Theoretical Frame for Clustering Fuzzy Relational Data
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/openAccess
dc.identifier.doi