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Título

Vector space model anonymization

AutorAbril, Daniel; Navarro-Arribas, Guillermo; Torra, Vicenç
Palabras clavePrivacy
Vector space model
Anonymization
Fecha de publicación23-oct-2013
EditorIOS Press
CitaciónArtificial Intelligence Research and Development, Proceedings of the 16th International Conference of the Catalan Association for Artificial Intelligence. Frontiers in Artificial Intelligence and Applications, vol. 256, 2013, pp. 141-150.
ResumenThe vector space model is a document set representation widely used in information retrieval and text mining. When we are dealing with confidential documents the use of this model should be restricted in order to preserve the confidentiality and anonymity of the original documents. Following this idea, we introduce a method to anonymize the document vector space, allowing thus the use of analytic techniques without disclosing private information. The proposed method is inspired by microaggregation, a popular technique used in statistical disclosure control, which ensures privacy by the satisfaction of the k-anonymity principle. © 2013 The authors and IOS Press. All rights reserved.
URIhttp://hdl.handle.net/10261/134112
DOI10.3233/978-1-61499-320-9-141
Identificadoresdoi: 10.3233/978-1-61499-320-9-141
issn: 09226389
isbn: 978-161499319-3
Aparece en las colecciones: (IIIA) Comunicaciones congresos
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