PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Testing Some Improvements of the Fukunaga and Narendra´s Fast Nearest Neighbour Search Algorithm in a Spelling Task
E. Gómez-Ballester, Luisa Mico and Jose Oncina
In: Pattern Recognition and Image Analysis Lecture Notes in Computer Science , LNCS 3523 . (2005) Springer Verlag , Berlin, Germany , pp. 3-10. ISBN 3 540 26154 0

Abstract

Nearest neighbour search is one of the most simple and used technique in Pattern Recognition. One of the most known fast nearest neighbour algorithms was proposed by Fukunaga and Narendra. The algorithm builds a tree in preprocess time that is traversed on search time using some elimination rules to avoid its full exploration. This paper tests two new types of improvements in a real data environment, a spelling task. The first improvement is a new (and faster to build) type of tree, and the second is the introduction of two new elimination rules. Both techniques, even taken independently, reduce significantly both: the number o distance computations and the search time expended to find the nearest neighbour.

EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:1567
Deposited By:Luisa Mico
Deposited On:28 November 2005