DocumentCode :
2370322
Title :
Fast PNN-based clustering using k-nearest neighbor graph
Author :
Fränti, Pasi ; Virmajoki, Olli ; Hautamäki, Ville
Author_Institution :
Dept. of Comput. Sci., Joensuu Univ., Finland
fYear :
2003
fDate :
19-22 Nov. 2003
Firstpage :
525
Lastpage :
528
Abstract :
Search for nearest neighbor is the main source of computation in most clustering algorithms. We propose the use of nearest neighbor graph for reducing the number of candidates. The number of distance calculations per search can be reduced from O(N) to O(k) or where N is the number of clusters, and k is the number of neighbors in the graph. We apply the proposed scheme within agglomerative clustering algorithm known as the PNN algorithm.
Keywords :
graph theory; search problems; statistical analysis; vector quantisation; PNN; agglomerative clustering algorithm; k-nearest neighbor graph; pairwise nearest neighbor; search problem; vector quantization; Clustering algorithms; Computer science; Costs; Distortion measurement; Iterative algorithms; Mean square error methods; Nearest neighbor searches; Optimization methods; Tree graphs; Vector quantization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Mining, 2003. ICDM 2003. Third IEEE International Conference on
Print_ISBN :
0-7695-1978-4
Type :
conf
DOI :
10.1109/ICDM.2003.1250968
Filename :
1250968
Link To Document :
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