Publicaciones

On the declassification of confidential documents

Tipo de Publicación:

Conference Proceedings

Autores:

Daniel Abril; Guillermo Navarro-Arribas; Vicenç Torra

Origen:

Modeling Decisions for Artificial Intelligence, MDAI 2011, Springer, Volumen6820, Changsha, China, p.235-246 (2011)

URL:

http://www.springerlink.com/content/tg81j807q42x8837/

Palabras clave:

declassification; anonymity; privacy preserving information retrieval; semantic; data privacy; information retrieval; pattern classification; named-entity recognition

Resumen:

Abstract. We introduce the anonymization of unstructured documents to settle the base of automatic declassification of confidential documents. Departing from known ideas and methods of data privacy, we introduce the main issues of unstructured document anonymization and propose the use of named entity recognition techniques from natural language processing and information extraction to identify the entities of the document that need to be protected.

Proyectos: 
ARES
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