Latent representation models for mining geo-spatial data - Liu, Yiding (Nanyang Technological University, 2020)
With the proliferation of mobile devices and location-based services (LBS), huge amounts of geo-spatial data (e.g., check-ins, points of interest, GPS traces) are becoming available from numerous sources. These data provides us unprecedented opportunities to uncover the complex semantics and dynamics of geographical space and human mobility. It is promising to develop data-driven approaches for harnessing geo-spatial data and discovering pivotal knowledge to support a wide spectrum of real-world applications, such as business analytics, spatial information retrieval, traffic management, etc.