Leveraging the linkedin social network data for extracting content-based user profiles
Pasquale Lops, Marco de Gemmis, Giovanni Maria Semeraro, Fedelucio Narducci, Cataldo Musto · 2011
In the last years, hundreds of social networks sites have been launched with both professional (e.g., LinkedIn) and non-professional (e.g., MySpace, Facebook) orientations. This resulted in a renewed information overload problem, but it also provided a new and unforeseen way of gathering useful, accurate and constantly updated information about user interests and tastes. Content-based recommender systems can leverage the wealth of data emerging by social networks for building user profiles in which representations of the user interests are maintained.