A R-tree-based Fine Directional Query Filtering

there have little work on processing joins with direction predicates, the research work on processing of spatial joins has primarily focused on topological and distance relations. The processing of direction relation queries is essentially a traversing process. A new fine query filtering method based on R-tree presented in this paper. A fine filtering step added in the middle of the traditional 2-stage query model. The improved method could decrease the size of candidate set in the filter step, and thus it can reduce the workload of the refine step. The validity of method is be proved by theoretical analysis. The improved methods only achieve the 40% calculation cost of original method. Results fully prove the validity of this method. Finally, it uses real world datasets to prove the validity. The experiment results show that performance evaluation of the proposed method performs well with respect to both I/O-and CPU-time.