Multidimensional binary search trees used for associative searching
Communications of the ACM
The nearest neighbour problem in information retrieval: an algorithm using upperbounds
SIGIR '81 Proceedings of the 4th annual international ACM SIGIR conference on Information storage and retrieval: theoretical issues in information retrieval
Theoretical and Empirical Analysis of ReliefF and RReliefF
Machine Learning
On k-Nearest Neighbor Voronoi Diagrams in the Plane
IEEE Transactions on Computers
Fast identification of visual documents using local descriptors
Proceedings of the eighth ACM symposium on Document engineering
International Journal of Approximate Reasoning
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An algorithm and data structure are presented for searching a file containing N records, each described by k real valued keys, for the m closest matches or nearest neighbors to a given query record. The computation required to organize the file is proportional to kNlogN. The expected number of records examined in each search is independent of the file size. The expected computation to perform each search is proportional to logN. Empirical evidence suggests that except for very small files, this algorithm is considerably faster than other methods.