|Title||On the use of At least $k$ fuzzy c-means in microaggregation: description and evaluation|
|Publication Type||Conference Paper|
|Year of Publication||2002|
|Authors||Domingo-Ferrer J, Torra V|
|Conference Name||Proc. of the Joint 1st Int. Conference on Soft Computing and Intelligent Systems and 3rd Int. Symposium on Advanced Intelligent Systems|
Microaggregation is a well-known masking method for microdata protection used by National Statistical Offices. Given a set of objects described in terms of a set of variables, this method consits on building a partition of the objects and then replace the original evaluation for each variable by the aggregates of each partition. This is, the values in a given cluster are aggregated – fused – and used instead of the original ones. As the problem of finding the best partition for microdata protection is an NP problem, heuristic methods are considered in the literature. In this work we describe an alternative approach based on fuzzy c-means.
- About IIIA
- Current news