Mining Human-Place Interaction Patterns from Location-Based Social Networks to Enrich Place Categorization Systems

Place categorization plays an important role in locationbased services as well as more recently in place-based geographic information systems. Traditionally, such categorization systems are often designed following a top-down approach in which a group of experts or users assign a place type, e.g. Restaurant, to a place instance, e.g., Bob’s BBQ shack. While the output of such a process generally satisfies the requirements of a particular application, it often fails to incorporate the perception of the general public towards places. In today’s online landscape, some parts of this perception are captured by location-based social network platforms. Contributions to these platforms, such as check-ins and reviews, enable a bottom-up approach to place categorization based on the actual interaction between humans and places. In this short paper, we outline selected advantages of a hybrid approach, which combines top-down and bottom-up methods to enhance place type hierarchies.