Skip to Main Content
In traditional reverse nearest-neighbor (RNN) search, the goal is to find the set of interest objects taking the query object as the nearest neighbor given that the interest objects and the query object have the same type. However, when the interest objects and the query object are of different types, this problem is called bichromatic reverse nearest neighbor (BRNN) search. The BRNN query has an increasing number of mobile applications and requires efficient algorithms for processing. In this paper, we present a novel approach for the BRNN search in the context of spatial network databases (SNDB). The main idea behind our approaches is to use Euclidean-based range search to prune the search space and use Euclidean distance in addition to network distance to minimize processing time. Finally, the experimental results confirm that our proposed algorithm have good performance on different network densities.