Name
Abstract | ||
|---|---|---|
The hierarchical clustering is an important method of clustering analysis. This kind of method can decompose the data into different levels, and the clustering result has a hierarchical coarseness to fine representation characteristic. In this paper, a new hierarchical clustering method based on GiST is proposed, which could store the structure of the tree generated during the clustering procedure in the hard disk. So it can support very detail analyzing procedure. The users can discover the relationship among clusters conveniently with this method. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-74282-1_15 | ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS: WITH ASPECTS OF CONTEMPORARY INTELLIGENT COMPUTING TECHNIQUES |
Keywords | Field | DocType |
GiST,hierarchical clustering,data mining,object-oriented technology | Hierarchical clustering,Canopy clustering algorithm,CURE data clustering algorithm,Pattern recognition,Correlation clustering,Computer science,Hierarchical clustering of networks,Artificial intelligence,Cluster analysis,Brown clustering,Single-linkage clustering | Conference |
Volume | ISSN | Citations |
2 | 1865-0929 | 0 |
PageRank | References | Authors |
0.34 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bing Zhou | 1 | 49 | 2.29 |
| He-xing Wang | 2 | 0 | 0.34 |
| Cuirong Wang | 3 | 70 | 7.03 |