Reverse Nearest Neighbor Search in Semantic Trajectories for Location-Based Services

In resource planning scenarios, reverse $k$ nearest neighbor search plays an important role. However, the existing on trajectories only supports spatial features of trajectories. this article, we introduce neighbors query semantic (R NNST). Given a point from set geo-textual objects (e.g., POIs), finds those that take as one their correlative objects. To efficiently answer R NNST queries, propose novel index IMC-tree, which organizes global and local information A branch-and-bound algorithm DOTA is then designed to traverse IMC-tree with various pruning rules. speed up computation distance, also design inverted-file-based compute without enumerating all combinations Experiments real dataset validate effectiveness efficiency our proposed algorithms.