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The vector space model is a document set representation widely used in information retrieval and text mining. When we are dealing with confidential documents the use of this model should be restricted in order to preserve the confidentiality and anonymity of the original documents. Following this idea, we introduce a method to anonymize the document vector space, allowing thus the use of analytic techniques without disclosing private information. The proposed method is inspired by microaggregation, a popular technique used in statistical disclosure control, which ensures privacy by the satisfaction of the k-anonymity principle.