Abstract
Given a set S of n data points in some metric space. Given a query point q in this space, a nearest neighbor query asks for the nearest point of S to q. Throughout we will assume that the space is real d-dimensional space Rd, and the metric is Euclidean distance. The goal is to preprocess S into a data structure so that such queries can be answered efficiently. Nearest neighbor searching has applications in many areas, including data mining [7], pattern classification [5], data compression [10].
The support of the National Science Foundation under grant CCR-9712379 is gratefully acknowledged.
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Maneewongvatana, S., Mount, D.M. (2001). The Analysis of a Probabilistic Approach to Nearest Neighbor Searching. In: Dehne, F., Sack, JR., Tamassia, R. (eds) Algorithms and Data Structures. WADS 2001. Lecture Notes in Computer Science, vol 2125. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44634-6_26
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DOI: https://doi.org/10.1007/3-540-44634-6_26
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