\( \newcommand{\E}{\mathrm{E}} \) \( \newcommand{\A}{\mathrm{A}} \) \( \newcommand{\R}{\mathrm{R}} \) \( \newcommand{\N}{\mathrm{N}} \) \( \newcommand{\Q}{\mathrm{Q}} \) \( \newcommand{\Z}{\mathrm{Z}} \) \( \def\ccSum #1#2#3{ \sum_{#1}^{#2}{#3} } \def\ccProd #1#2#3{ \sum_{#1}^{#2}{#3} }\)
CGAL 4.5.2 - dD Spatial Searching
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Bibliographic References
[1]

S. Arya and D. M. Mount. Algorithms for fast vector quantization. In Data Compression Conference, pages 381–390. IEEE Press, 1993.

[2]

S. Arya and D. M. Mount. Approximate nearest neighbor queries in fixed dimensions. In Proc. 4th ACM-SIAM Sympos. Discrete Algorithms, pages 271–280, 1993.

[3]

J. L. Bentley. Multidimensional binary search trees used for associative searching. Commun. ACM, 18(9):509–517, September 1975.

[4]

J. H. Friedman, J. L. Bentley, and R. A. Finkel. An algorithm for finding best matches in logarithmic expected time. ACM Trans. Math. Softw., 3:209–226, 1977.

[5]

G. R. Hjaltason and H. Samet. Ranking in spatial databases. In M. J. Egenhofer and J. R. Herring, editors, Advances in Spatial Databases - Fourth International Symposium, number 951 in Lecture Notes Comput. Sci., pages 83–95, August 1995.