The usage of social networks sites (SNSs), such as Facebook, and geosocial networks (GSNs), such as Foursquare, has increased tremendously over the past years. The willingness of users to share their current locations and experiences facilitate the creation of geographical recommender systems based on user generated content (UGC). This idea has been used to create a substantial amount of geosocial recommender systems (GRSs), such as Gogobot, TripIt, and Trippy already, but can be applied to more complex scenarios, such as the recommendation of products with a strong binding to their region, such as real estate or vacation destinations.
This extended form of GRS development requires advanced functionality for information collection (from the web, other social media and sensors), information enrichment (such as data quality assessment and advanced data analysis), and personalized recommendations. The creation of a toolset to cope with these challenges is the goal of this research project, for which the outline is presented in this paper.