Issue No. 02 - Feb. (2013 vol. 25)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TKDE.2011.230
Marco Vanetti , University of Insubria, Varese
Elisabetta Binaghi , University of Insubria, Varese
Elena Ferrari , University of Insubria, Varese
Barbara Carminati , University of Insubria, Varese
Moreno Carullo , University of Insubria, Varese
One fundamental issue in today's Online Social Networks (OSNs) is to give users the ability to control the messages posted on their own private space to avoid that unwanted content is displayed. Up to now, OSNs provide little support to this requirement. To fill the gap, in this paper, we propose a system allowing OSN users to have a direct control on the messages posted on their walls. This is achieved through a flexible rule-based system, that allows users to customize the filtering criteria to be applied to their walls, and a Machine Learning-based soft classifier automatically labeling messages in support of content-based filtering.
Access control, Feature extraction, Facebook, Semantics, Text categorization, Graphical user interfaces, policy-based personalization, Online social networks, information filtering, short text classification
M. Carullo, B. Carminati, E. Ferrari, E. Binaghi and M. Vanetti, "A System to Filter Unwanted Messages from OSN User Walls," in IEEE Transactions on Knowledge & Data Engineering, vol. 25, no. , pp. 285-297, 2013.