Spatial Bayesian Learning Algorithms for Geographic Information Retrieval Arron R, Walker, Binh Pham, and Miles Moody   View Paper (PDF)   Return to Session 3: Data Integration and Data Mining Abstract An increasing amount of freely available Geographic Information System (GIS) data on the Internet has stimulated recent research into Geographic Information Retrieval (GIR). Typically, GIR looks at the problem of retrieving GIS datasets on a theme by theme basis. However in practice, themes are generally not analysed in isolation. More often than not multiple themes are required to create a map for a particular analysis task. To do this using the current GIR techniques, each theme is retrieved o ... ©2006 Association for Computing Machinery