Title | Spherical microaggregation: Anonymizing sparse vector spaces |
Publication Type | Journal Article |
Year of Publication | 2015 |
Authors | Abril D, Navarro-Arribas G, Torra V |
Journal | Computers & Security |
Volume | 49 |
Pagination | 17 |
Publisher | Elsevier |
Keywords | anonymization, data mining, sparse data, vector space |
Abstract | Abstract Unstructured texts are a very popular data type and still widely unexplored in the privacy preserving data mining field. We consider the problem of providing public information about a set of confidential documents. To that end we have developed a method to protect a Vector Space Model (VSM), to make it public even if the documents it represents are private. This method is inspired by microaggregation, a popular protection method from statistical disclosure control, and adapted to work with sparse and high dimensional data sets. |
URL | http://www.sciencedirect.com/science/article/pii/S0167404814001679 |