Discovery of General Knowledge in Large Spatial Databases

Abstract

Extraction of interesting and general knowledge from large spatial databases is an important task in the development of spatial data- and knowledge-base systems. In this paper, we investigate knowledge discovery in spatial databases and develop a generalization-based knowledge discovery mechanism which integrates attribute-oriented induction on nonspatial data and spatial merge and generalization on spatial data. The study shows that knowledge discovery has wide applications in spatial databases, and relatively efficient algorithms can be developed for discovery of general knowledge in large spatial databases. 1. Introduction Spatial reasoning using data and knowledge stored in large spatial databases is a crucial task in the development of geographical information systems, medical imaging and robotics systems. Because of the huge amount (usually, tera-bytes) of spatial data obtained from satellites, video cameras, medical equipments, etc., it is costly and often unrealistic for users...