Title
Combining Multiple Clustering Methods Based on Core Group
Abstract
As an unsupervised technique, clustering analysis has been widely applied in various fields. However, it is usually difficult to select an appropriate clustering method for an application, while no clustering method is suitable for all situations. This paper proposes a novel method to combine multiple clustering methods. First, the paper combines different agglomerative hierarchical methods in one clustering process to obtain core groups. Core group refers to the data that are always clustered together no matter what clustering method is applied. Then, it adopts other kind of clustering methods to refine the core groups and index database. In addition to conduct a series of experiments on the datasets from UCI, the paper applies the proposed method in a new research field, 3D model retrieval, to analyze and index the 3D model database.
Year
DOI
Venue
2006
10.1109/SKG.2006.34
SKG
Keywords
Field
DocType
cluster analysis,indexation
Hierarchical clustering,Data mining,Canopy clustering algorithm,Fuzzy clustering,Data stream clustering,Correlation clustering,Computer science,Cluster analysis,Brown clustering,Single-linkage clustering
Conference
Volume
Issue
ISBN
null
null
0-7695-2673-X
Citations 
PageRank 
References 
2
0.39
7
Authors
4
Name
Order
Citations
PageRank
Lv Tianyang1338.49
Shaobin Huang2117.93
Xi-zhe Zhang3388.94
Zhengxuan Wang44713.93