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Título

On the connections between statistical disclosure control for microdata and some artificial intelligence tools

AutorDomingo-Ferrer, Josep; Torra, Vicenç
Palabras claveStatistical disclosure control
Re-identification procedures
Official statistics
Data cleaning
Synthesis of information
Data mining
Artificial intelligence
Fecha de publicación2003
EditorElsevier
CitaciónInformation Sciences 151: 153- 170 (2003)
ResumenStatistical disclosure control (SDC) and artificial intelligence (AI) use similar tools for different purposes. This work describes the common elements of both areas to increase their synergy. SDC is a discipline that seeks to modify statistical data so that they can be published (typically by National Statistical Offices) without giving away the identity of any individual behind the data. When dealing with individual data (microdata in SDC jargon), both SDC procedures and AI knowledge integration procedures use similar principles for different purposes (masking data vs. improving its quality). Similarities can also be found for methods evaluating re-identification risk in SDC and data mining tools for making data consistent. This paper explores those methodological connections with the aim of stimulating interaction between both fields. In particular, data mining turns out to be a common interest of both fields. © 2003 Elsevier Science Inc. All rights reserved.
URIhttp://hdl.handle.net/10261/161147
Identificadoresdoi: 10.1016/S0020-0255(03)00064-1
issn: 0020-0255
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