Publicaciones

Towards privacy preserving information retrieval through semantic microaggregation

Tipo de Publicación:

Conference Proceedings

Autores:

Daniel Abril; Guillermo Navarro-Arribas; Vicenç Torra

Origen:

Web Intelligence and Intelligent Agent Technology (WI-IAT), 2010 IEEE/WIC/ACM International Conference on, IEEE, Volumen3, Toronto, Canada, p.296 - 299 (2010)

ISBN:

978-1-4244-8482-9

URL:

http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5614556

Palabras clave:

Web indexing task; classification task; frequency term vector; k-anonymity preservation; privacy preserving information retrieval; semantic microaggregation; Internet; data privacy; information retrieval; pattern classification; vectors

Resumen:

In this paper we introduce the problem of providing privacy preserving information for Web indexing, classification, and other information retrieval task. Web pages are represented by a frequency term vector that preserves k-anonymity for all the Web pages. This vector can then be used, for example, to build indexes of classifiers. Our proposal makes use of semantic micro aggregation.

Proyectos: 
ARES
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