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Conference papers
Approaches of anonymisation of an SMS corpus
Abstract : This paper presents two anonymisation methods to process an SMS corpus. The first one is based on an unsupervised approach called Seek&Hide. The implemented system uses several dictionaries and rules in order to predict if a SMS needs anonymisation process. The second method is based on a supervised approach using machine learning techniques. We evaluate the two approaches and we propose a way to use them together. Only when the two methods do not agree on their prediction, will the SMS be checked by a human expert. This greatly reduces the cost of anonymising the corpus.
Cited literature [15 references]
https://hal-lirmm.ccsd.cnrs.fr/lirmm-00816285
Contributor : Mathieu Roche <>
Submitted on : Friday, February 24, 2017 - 6:22:43 PM
Last modification on : Thursday, February 7, 2019 - 2:50:12 PM
Document(s) archivé(s) le : Thursday, May 25, 2017 - 2:20:30 PM
Contributor : Mathieu Roche <>
Submitted on : Friday, February 24, 2017 - 6:22:43 PM
Last modification on : Thursday, February 7, 2019 - 2:50:12 PM
Document(s) archivé(s) le : Thursday, May 25, 2017 - 2:20:30 PM
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