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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Approaches of Anonymisation of an SMS Corpus
verfasst von : Namrata Patel, Pierre Accorsi, Diana Inkpen, Cédric Lopez, Mathieu Roche
Erschienen in: Computational Linguistics and Intelligent Text Processing
Verlag: Springer Berlin Heidelberg
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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.