DocumentCode
2711463
Title
Intrinsic Cluster Detection Using Adaptive Grids
Author
Sarmah, S. ; Das, R. ; Bhattacharyya, D.K.
Author_Institution
Tezpur Univ., Assam
fYear
2007
fDate
18-21 Dec. 2007
Firstpage
371
Lastpage
376
Abstract
This paper presents an algorithm GDCT, grid density clustering using triangle-subdivision, capable of identifying arbitrary shaped embedded clusters as well as multi density clusters over large spatial datasets. The experimental results establish the superiority of the technique in terms of cluster quality.
Keywords
pattern clustering; very large databases; visual databases; adaptive grids; arbitrary shaped embedded clusters; grid density clustering; intrinsic cluster detection; large spatial datasets; multidensity clusters; triangle-subdivision; Clustering algorithms; Degradation; Embedded computing; Grid computing; Multi-stage noise shaping; Multidimensional systems; Nearest neighbor searches; Optical sensors; Partitioning algorithms; Shape;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Computing and Communications, 2007. ADCOM 2007. International Conference on
Conference_Location
Guwahati, Assam
Print_ISBN
0-7695-3059-1
Type
conf
DOI
10.1109/ADCOM.2007.18
Filename
4425999
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