Name
Title | ||
|---|---|---|
Document Clustering Algorithm Based on Tree-Structured Growing Self-Organizing Feature Map |
Abstract | ||
|---|---|---|
Document clustering is widely studied in text: mining. In this paper, document clustering algorithm based on Tree-Structured Growing Self-organizing Feature Map (TGSOM) is presented as an extended version of the clustering algorithm of Self-organizing Map (SOM) in neural network, which has a dynamic tree-structure generated during the training process. TGSOM 's growth speed can be controlled through the function of the Spread Factor (SF), and the precision of clustering results is different because of the difference value of SF. The user can get the hierarchical clustering results through changing the size of SF in different steps during clustering. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/978-3-540-28647-9_138 | ADVANCES IN NEURAL NETWORKS - ISNN 2004, PT 1 |
Keywords | Field | DocType |
tree structure,neural network,text mining,document clustering,hierarchical clustering | Fuzzy clustering,Data mining,CURE data clustering algorithm,Computer science,Artificial intelligence,Cluster analysis,Single-linkage clustering,Hierarchical clustering,Canopy clustering algorithm,Data stream clustering,Pattern recognition,Correlation clustering,Algorithm,Machine learning | Conference |
Volume | ISSN | Citations |
3173 | 0302-9743 | 1 |
PageRank | References | Authors |
0.37 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaoshen Zheng | 1 | 4 | 2.93 |
| Wenling Liu | 2 | 3 | 2.21 |
| Pilian He | 3 | 29 | 7.46 |
| Weidi Dai | 4 | 13 | 2.96 |