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.
Links:
[1] http://www.iiia.csic.es/en/individual/daniel-abril
[2] http://www.iiia.csic.es/en/individual/guillermo-navarro-arribas
[3] http://www.iiia.csic.es/en/individual/vicenc-torra
[4] http://www.springerlink.com/content/tg81j807q42x8837/
[5] http://www.iiia.csic.es/en/publications/keyword/declassification
[6] http://www.iiia.csic.es/en/publications/keyword/anonymity
[7] http://www.iiia.csic.es/en/publications/keyword/privacy preserving information retrieval
[8] http://www.iiia.csic.es/en/publications/keyword/semantic
[9] http://www.iiia.csic.es/en/publications/keyword/data privacy
[10] http://www.iiia.csic.es/en/publications/keyword/information retrieval
[11] http://www.iiia.csic.es/en/publications/keyword/pattern classification
[12] http://www.iiia.csic.es/en/publications/keyword/named-entity recognition
[13] http://www.iiia.csic.es/en/publications/export/tagged/4440
[14] http://www.iiia.csic.es/en/publications/export/xml/4440
[15] http://www.iiia.csic.es/en/publications/export/bib/4440
[16] http://www.iiia.csic.es/en/project/ares