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
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;
Conference_Titel :
Fuzzy Systems (FUZZ), 2011 IEEE International Conference on
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-7315-1
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZY.2011.6007447
