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Semantic‐based aggregation for statistical disclosure control
Author(s) -
Valls Aïda,
Torra Vicenç,
Domingo Josep
Publication year - 2003
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.10129
Subject(s) - categorical variable , computer science , aggregate (composite) , cluster analysis , data mining , confidentiality , set (abstract data type) , information retrieval , publication , data set , order (exchange) , control (management) , artificial intelligence , machine learning , computer security , programming language , materials science , finance , advertising , economics , business , composite material
In this paper we show how clustering can be used to aggregate different versions of the same data set in order to discover confidential information. Having these tools helps to not publish data that could be reidentified, which is known as Statistical Disclosure Control. In particular, the paper is focused on the case of dealing with categorical values. © 2003 Wiley Periodicals, Inc.