On intuitionistic fuzzy clustering for its application to privacy

Author

Torra, Vicenc ; Miyamoto, Sadaaki ; Endo, Yasunori ; Domingo-Ferrer, Josep

Author_Institution

Inst. d´´Investigacio en Intel-ligencia Artificial, CSIC, Bellaterra

fYear

2008

fDate

1-6 June 2008

Firstpage

1042

Lastpage

1048

Abstract

Motivated by our research on specific information loss measures (in privacy preserving data mining) and our need to compare fuzzy clusters, we proposed in a recent paper a definition for intuitionistic fuzzy partitions. We showed how to define them in the framework of fuzzy clustering. That is, we introduced a method to define intuitionistic fuzzy partitions from the results of fuzzy clustering. In this paper we further study such intuitionistic fuzzy partitions and we extend our previous results with other types of fuzzy clustering algorithms.

Keywords

data mining; data privacy; fuzzy set theory; pattern clustering; data mining; information loss measures; intuitionistic fuzzy clustering; Clustering algorithms; Clustering methods; Data privacy; Distortion measurement; Fuzzy sets; Loss measurement; Machine learning algorithms; Partitioning algorithms; Protection; Systems engineering and theory;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on

Conference_Location

Hong Kong

ISSN

1098-7584

Print_ISBN

978-1-4244-1818-3

Electronic_ISBN

1098-7584

Type

conf

DOI

10.1109/FUZZY.2008.4630498

Filename

4630498