Spherical Microaggregation: Anonymizing Sparse Vector Spaces
2015 (Engelska)Ingår i: Computers & security (Print), ISSN 0167-4048, E-ISSN 1872-6208, Vol. 49, s. 28-44Artikel i tidskrift (Refereegranskat) Published
Abstract [en]
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.
Ort, förlag, år, upplaga, sidor
Elsevier, 2015. Vol. 49, s. 28-44
Nationell ämneskategori
Elektroteknik och elektronik
Forskningsämne
Teknik; Skövde Artificial Intelligence Lab (SAIL)
Identifikatorer
URN: urn:nbn:se:his:diva-10653DOI: 10.1016/j.cose.2014.11.005ISI: 000350519300003Scopus ID: 2-s2.0-84918506621OAI: oai:DiVA.org:his-10653DiVA, id: diva2:787893
Forskningsfinansiär
EU, FP7, Sjunde ramprogrammet2015-02-122015-02-122018-03-28Bibliografiskt granskad