A Branch and Bound Algorithm for Computing k-Nearest Neighbors
IEEE Transactions on Computers
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This paper presents a new fast algorithm for the determination among a M-dimensional set of points the neighbor nearest a given point by using the Euclidean metric space. Two steps are needed. First, a region which contains the unknown point and at least one neighbor is found by utilising an ordered search procedure of the unknown point from Oi i=l..g reference points. Second, the found region is modified such that the nearest neighbor to the given point will be inside it. The nearest neighbor is then determined at the expense of a small number of distance calculations. The number g and the positions of the reference points are determined properly taking into account the structure of the initial set of points and keeping the search region always to a minimum. The preproccesing load is considered as moderate and real experiments demonstrate the fast and accurate of the algorithm.