HEURISTIC EXTENDED SEARCH EXPANSION ALGORITHM BASED ON TRAJECTORY QUERY WITH SEQUENTIAL INTEREST REGIONS

摘要

Disclosed in the present invention is a heuristic extended search expansion algorithm based on a trajectory query with sequential interest regions, comprising the following steps: step 1, initially setting a lower bound LB=0 for a global spatial density correlation and an upper bound UB=+∞ for the global spatial density correlation; step 2, selecting a group of query sources from a query region center; step 3, initially setting the priority of all the query sources to 0, and performing heuristic searching based on priority ranking from each query source; step 4, calculating the upper bound and lower bound of a spatial density, and updating LB and UB; step 5, determining whether LB is greater than UB or whether all search radii exceed ε+p.dist/2, if yes, entering the next step, and if not, returning to the previous step; step 6, sorting trajectories according to the value of the upper bound of the spatial density; and step 7, performing refinement according to the trajectory sequence, and returning a trajectory with a maximal spatial density correlation. According to the present invention, the problem that conventional trajectory searching is invalid for TSR querying is resolved, the search space is reduced, the traversal of overlapping regions is avoided, the query performance is improved, and the TSR query with a sequence is effectively processed.