TitleTowards Semantic Microaggregation of Categorical Data for Confidential Documents
Publication TypeConference Proceedings
Year of Conference2010
AuthorsAbril D, Navarro-Arribas G, Torra V
Editor
Volume6408
PublisherSpringer
Pagination266-276
Conference LocationPerpignan, France
Date Published27-08-2010
Keywordsclassification task, Data Privacy, frequency term vector, Information Retrieval, Internet, k-anonymity preservation, pattern classification, privacy preserving information retrieval, semantic microaggregation, vectors, Web indexing task
Abstract

In the data privacy context, specifically, in statistical disclosure control techniques, microaggregation is a well-known microdata protection method, ensuring the confidentiality of each individual. In this paper, we propose a new approach of microaggregation to deal with semantic sets of categorical data, like text documents. This method relies on the WordNet framework that provides complete semantic relationship taxonomy between words. Therefore, this extension aims ensure the confidentiality of text documents, but at the same time, it should preserve the general meaning. We apply some measures to evaluate the quality of the protection method relying on information loss.

URLhttp://www.springerlink.com/content/f41402862155w6t4/