A Taxonomy of Recommender Agents on theInternet
Artificial Intelligence Review
Learning to identify emotions in text
Proceedings of the 2008 ACM symposium on Applied computing
GeoLife2.0: A Location-Based Social Networking Service
MDM '09 Proceedings of the 2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware
Trajectory simplification method for location-based social networking services
Proceedings of the 2009 International Workshop on Location Based Social Networks
Learning Location Correlation from GPS Trajectories
MDM '10 Proceedings of the 2010 Eleventh International Conference on Mobile Data Management
Towards location-based social networking services
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Location Based Social Networks
Point of interest to region of interest conversion
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
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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 allowing the users to supply UGC inside the application), 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.