Data Stream Clustering Algorithm Based on Active Grid Density

Author

Yang, Jing ; Zhu, Wenxin ; Zhang, Jianpei ; Yang, Yue

Author_Institution

Coll. of Comput. Sci. & Technol., Harbin Eng. Univ., Harbin, China

fYear

2010

fDate

1-2 Nov. 2010

Firstpage

97

Lastpage

101

Abstract

CluStream is a representative data stream cluster algorithm, however, it is not able to find arbitrary clusters in shape and deal with boundary points effectively. A new algorithm which is based on active grid density AGD-Stream is proposed to solve these problems in this paper. The algorithm adopts a density decaying technology to capture the dynamic of data stream, and extracts the boundary point of grid to delete. Besides, this paper uses activity concept to judge activity of the grid density, neglecting the inactive grid density and preserving the active gird density for clustering. Experiment shows that AGD-Stream can not only find arbitrary clusters in shape, but also deal with boundary points. Compared with CluStream, AGD-Stream is better in time complexity and accuracy.

Keywords

computational complexity; data mining; pattern clustering; AGD-stream; active grid density; data mining; data stream clustering algorithm; density decaying technology; judge activity; time complexity; Accuracy; Algorithm design and analysis; Clustering algorithms; Complexity theory; Data mining; Heuristic algorithms; Shape; data mining; dual confidence; minimum correlation; negative association rules; positive;

fLanguage

English

Publisher

ieee

Conference_Titel

Internet Computing for Science and Engineering (ICICSE), 2010 Fifth International Conference on

Conference_Location

Heilongjiang

Print_ISBN

978-1-4244-9954-0

Type

conf

DOI

10.1109/ICICSE.2010.12

Filename

6076549