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