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Reverse nearest neighbor (RNN) queries have a broad application base such as decision support, profile-based marketing, resource allocation, data mining, etc. Previous work on RNN search does not take obstacles into consideration. In the real world, however, there are many physical obstacles (e.g., buildings, blindages, etc.), and their presence may affect the visibility/distance between two objects...
Given a set of trajectories D, a query object (point or trajectory) q, and a query interval T, a mutual (i.e., symmetric) nearest neighbor (MNN) query over trajectories finds from D within T, the set of trajectories that are among the k1 nearest neighbors (NNs) of q, and meanwhile, have q as one of their k2 NNs. This type of queries considers proximity of q to the trajectories and the proximity of...
Given two sets DA and DB of multidimensional objects, a spatial region R, and a critical distance dc, an optimal-nearest- neighbor (ONN) query retrieves outside R, the object in DB with maximum optimality. Let CAR (Sp,p) be the cardinality of the subset Sp of objects in DA which locate within R and are enclosed by the vicinity circle centered at p with radius dc. Then, an object o is said to be better...
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