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Privacy-Preserving Enhanced Collaborative Tagging
Jan. 2014 (vol. 26 no. 1)
pp. 180-193
Javier Parra-Arnau, Universitat Politècnica de Catalunya, Barcelona
Andrea Perego, Joint Research Centre of the European Commission, Ispra
Elena Ferrari, University of Insubria, Varese
Jordi Forne, Universitat Politècnica de Catalunya, Barcelona
David Rebollo-Monedero, Universitat Politècnica de Catalunya, Barcelona
Collaborative tagging is one of the most popular services available online, and it allows end user to loosely classify either online or offline resources based on their feedback, expressed in the form of free-text labels (i.e., tags). Although tags may not be per se sensitive information, the wide use of collaborative tagging services increases the risk of cross referencing, thereby seriously compromising user privacy. In this paper, we make a first contribution toward the development of a privacy-preserving collaborative tagging service, by showing how a specific privacy-enhancing technology, namely tag suppression, can be used to protect end-user privacy. Moreover, we analyze how our approach can affect the effectiveness of a policy-based collaborative tagging system that supports enhanced web access functionalities, like content filtering and discovery, based on preferences specified by end users.
Index Terms:
Privacy,Collaboration,Entropy,Semantics,Tag clouds,Data privacy,privacy-utility tradeoff,Policy-based collaborative tagging,social bookmarking,tag suppression,privacy-enhancing technology,Shannon's entropy
Citation:
Javier Parra-Arnau, Andrea Perego, Elena Ferrari, Jordi Forne, David Rebollo-Monedero, "Privacy-Preserving Enhanced Collaborative Tagging," IEEE Transactions on Knowledge and Data Engineering, vol. 26, no. 1, pp. 180-193, Jan. 2014, doi:10.1109/TKDE.2012.248
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