Discovery of Spatio-Temporal Patterns from Location Based Social Networks
Bejar Javier, Sergio Álvarez-Napagao, Garcia Dario, Gomez Ignasi, Oliva Luis, Tejeda Arturo, Javier Vázquez-Salceda · Frontiers in artificial intelligence and applications · 2014
Location Based Social Networks (LBSN) have become an interesting source for mining user behavior. These networks (e.g. Twitter, Instagram or Foursquare) collect spatio-temporal data from users in a way that they can be seen as a set of collective and distributed sensors on a geographical area. Processing this information in different ways could result in patterns useful for several application domains. These patterns include simple or complex user visits to places in a city or groups of users that can be described by a common behavior. The domains of application range from the recommendation of points of interest to visit and route planning for touristic recommender systems to city analysis and planning.