Paper Info
Title
The Role of Ontologies in the Anonymization of Textual Variables
Abstract
The exploitation of sensible data associated to individuals requires a proper anonymization in order to preserve the privacy. Even though several masking methods have been designed for numerical data, very few of them deal with textual information. During the masking process, information loss should be minimized in order to enable a proper analysis of data with data mining methods. In the case of textual data, the quality of the anonymized dataset is closely related to the preservation of semantics, a dimension which has been only shallowly considered in some previous works, by using small and ad-hoc hierarchies of words. In this work we want to study the use of large and standard ontologies as the base to perform the anonymization of textual variables. We will evaluate the role of ontologies in preserving the utility of the anonymized information when a partition of the objects is done with unsupervised clustering methods. Results show that by exploiting detailed ontologies, one is able to improve the preservation of the data semantics in comparison to approaches based on ad-hoc structures and data distribution metrics.
Year
DOI
Venue
2010
10.3233/978-1-60750-643-0-153
CCIA
Keywords
Field
DocType
textual variable,data mining method,data distribution metrics,textual data,numerical data,sensible data,information loss,textual information,data semantics,textual variables,anonymized information
Ontology (information science),Information loss,Information retrieval,Data analysis,Computer science,Textual information,Data semantics,Hierarchy,Cluster analysis,Semantics
Conference
Volume
ISSN
Citations 
220
0922-6389
5
PageRank 
References 
Authors
0.47
15
4
Name
Order
Citations
PageRank
Sergio Martínez116713.34
David Sánchez239913.21
Aïda Valls329838.71
Montserrat Batet489937.20