DocumentCode :
2219326
Title :
An Incremental Clustering Algorithm Based on Subcluster Feature
Author :
Meng, Hai-Dong ; Song, Yu-Chen ; Wang, Shu-Ling
Author_Institution :
Inner Mongolia Univ. of Sci. & Technol., Baotou, China
fYear :
2009
fDate :
26-28 Dec. 2009
Firstpage :
786
Lastpage :
789
Abstract :
For very large databases, such as spatial database and multimedia database, the traditional clustering algorithms are of limitations in validity and scalability. According to the notion of clustering feature of BIRCH, an incremental clustering algorithm is designed and implemented, which solves the problems of effectiveness, space and time complexities of clustering algorithms for very large spatial databases. Theoretic analysis and experimental results demonstrate that the incremental clustering algorithm cannot only handle very large spatial databases, but also has good performance.
Keywords :
multimedia databases; pattern clustering; very large databases; visual databases; BIRCH; incremental clustering algorithm; multimedia database; space complexities; spatial database; subcluster feature; time complexities; very large databases; Algorithm design and analysis; Clustering algorithms; Image databases; Multimedia databases; Partitioning algorithms; Performance analysis; Sampling methods; Shape; Space technology; Spatial databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Engineering (ICISE), 2009 1st International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4909-5
Type :
conf
DOI :
10.1109/ICISE.2009.282
Filename :
5455002
Link To Document :
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