Towards a crowdsourced supervision of the analysis of user-generated geographic content: Engaging citizens in discovering urban places - Ostermann, F. O. (2020)
This paper presents a conceptual model and a proof-of-concept implementation of a novel approach to engage citizens in supervising the analysis of user-generated geographic content (UGGC).The complexity of some tasks and the increasing volume of UGGC often restrict the role of citizens to data providers. We propose a hybrid processing approach, which maps geographical problems into data mining and machine-learning tasks, presents analysis results to human supervisors, and uses the responses to improve the machine-learning and data mining. For the pilot study, we adapt an approach to find semantically distinct places in UGGC.