DocumentCode
3119154
Title
On some clustering approaches for graphs
Author
Stokes, Klara ; Torra, Vicenç
Author_Institution
Dept. of Comput. Eng. & Math., Univ. Rovira i Virgili, Tarragona, Spain
fYear
2011
fDate
27-30 June 2011
Firstpage
409
Lastpage
415
Abstract
In this paper we discuss some tools for graph perturbation with applications to data privacy. We present and analyse two different approaches. One is based on matrix decomposition and the other on graph partitioning. We discuss these methods and show that they belong to two traditions in data protection: noise addition/microaggregation and k-anonymity.
Keywords
data privacy; graph theory; matrix decomposition; clustering approach; data privacy; data protection; graph partitioning; graph perturbation; k-anonymity; matrix decomposition; noise addition; noise microaggregation; Correlation; Data privacy; Eigenvalues and eigenfunctions; Matrix decomposition; Media; Singular value decomposition; Symmetric matrices; Data privacy; clustering; graph; k-anonymity; microaggregation;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems (FUZZ), 2011 IEEE International Conference on
Conference_Location
Taipei
ISSN
1098-7584
Print_ISBN
978-1-4244-7315-1
Electronic_ISBN
1098-7584
Type
conf
DOI
10.1109/FUZZY.2011.6007447
Filename
6007447
Link To Document