Name
Abstract | ||
|---|---|---|
Many real applications, such as network traffic monitoring, intrusion detection, satellite remote sensing, and electronic business, generate data in the form of a stream arriving continuously at high speed. Clustering is an important data analysis tool for knowledge discovery. Compared with traditional clustering algorithms, clustering stream data is an important and challenging problem which has attracted many researchers. Clustering stream data is facing two main challenges. First, as the data is continuously arriving with high rate and the computer storage capacity is limited, raw data can only be scaned in one pass. Second, stream data is always changing with time, so viewing a data stream as a set of static data can deteriorate the clustering quality. In fact, users are more concerned with the evolving behaviors of clusters which can help people making correct decisions. This paper proposes a density-grid based clustering algorithm, PKS-Stream-I, for stream data. It is an optimization of PKS-Stream in density detection period selection, sporadic grid detection and removal. Empirical results show the proposed method yields out better performance. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/PDCAT.2012.13 | PDCAT |
Keywords | Field | DocType |
pattern clustering,raw data,clustering algorithm,density-grid,density-grid based clustering algorithm,clustering stream data,grid computing,traditional clustering algorithm,stream data,index tree,sporadic grid removal,sporadic grid detection,clustering,data analysis tool,knowledge discovery,important data analysis tool,pks-stream-i algorithm,stream data clustering,static data,data stream,clustering quality,density detection period selection | Fuzzy clustering,Data mining,Canopy clustering algorithm,CURE data clustering algorithm,Data stream mining,Data stream clustering,Correlation clustering,Computer science,Determining the number of clusters in a data set,Real-time computing,Cluster analysis | Conference |
ISBN | Citations | PageRank |
978-0-7695-4879-1 | 2 | 0.36 |
References | Authors | |
6 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dandan Zhang | 1 | 2 | 0.36 |
| Hui Tian | 2 | 66 | 11.33 |
| Yingpeng Sang | 3 | 21 | 9.05 |
| Yidong Li | 4 | 151 | 43.42 |
| Yanbo Wu | 5 | 74 | 6.53 |
| Jun Wu | 6 | 125 | 15.66 |
| Hong Shen | 7 | 499 | 52.98 |