Constrained k-closest pairs query processing based on growing window in crime databases

摘要: Spatial analysis in crime databases has recently been an active research topic. To solve the problem of finding closest pairs objects within a given spatial region, as required geo-data applications, this paper proposes efficient constrained k-closest query processing algorithm based on growing window. It expands window gradually instead searching whole workspace for multiple types objects. employs density-based range estimation approach to calculate square and optimized R-tree store index entities. In addition, distance threshold T pair is introduced prune tree nodes. Experiments evaluate effect three important factors, i.e., portion overlapping between workspaces two data sets, value k, size buffer. The results show that new outperforms heap-based approach.