DocumentCode :
3036888
Title :
A Clustering Algorithm Based on Symmetric Neighborhood of Micro-clusters
Author :
Zhang, Yu ; Pi, Dechang
Author_Institution :
Coll. of Inf. Sci. & Technol., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing
fYear :
2009
fDate :
8-10 March 2009
Firstpage :
118
Lastpage :
122
Abstract :
Clustering is an important task in data mining with numerous applications, including minefield detection, seismology, astronomy, etc. At present, the academic communities have introduced various clustering algorithms, and these methods have been widely applied to different fields according to their respective characteristics. In this paper, we propose a novel clustering algorithm based on symmetric neighborhood of micro-clusters in large database. Firstly we use k-means algorithm to produce micro-clusters which are introduced to compress the data, and then calculate both neighbors and reverse neighbors of micro-clusters to estimate their densities distribution, and gain the ultimate clustering result. The algorithm can discover arbitrary shape and different densities, and also it needs fewer input parameters than the existing clustering algorithms, such as, k-means algorithm. The efficiencies and effectiveness of the algorithm are validated through the test of IRIS testing dataset and synthetic dataset.
Keywords :
data mining; database management systems; pattern clustering; IRIS testing dataset; arbitrary shape; clustering algorithm; data mining; k-means algorithm; large database; microclusters; symmetric neighborhood; synthetic dataset; Clustering algorithms; Data analysis; Data mining; Databases; Educational institutions; Electronic mail; Information science; Partitioning algorithms; Space technology; Testing; clustering; data mining; micro-clusters; symmetric neighborhood;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer and Automation Engineering, 2009. ICCAE '09. International Conference on
Conference_Location :
Bangkok
Print_ISBN :
978-0-7695-3569-2
Type :
conf
DOI :
10.1109/ICCAE.2009.27
Filename :
4804500
Link To Document :
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