Research Article
Clustering Hierarchical Data Using SOM Neural Network
392 downloads
@INPROCEEDINGS{10.1007/978-3-642-36642-0_28, author={Le Tu and Nguyen Hoan and Le Thai}, title={Clustering Hierarchical Data Using SOM Neural Network}, proceedings={Context-Aware Systems and Applications. First International Conference, ICCASA 2012, Ho Chi Minh City, Vietnam, November 26-27, 2012, Revised Selected Papers}, proceedings_a={ICCASA}, year={2013}, month={2}, keywords={neural network kohonen self organizing map clustering data data mining}, doi={10.1007/978-3-642-36642-0_28} }- Le Tu
Nguyen Hoan
Le Thai
Year: 2013
Clustering Hierarchical Data Using SOM Neural Network
ICCASA
Springer
DOI: 10.1007/978-3-642-36642-0_28
Abstract
This paper proposes a solution for clustering hierarchical data using SOM neural network. The training process that combines data-partition and network-partition allows forming an automated hierarchical tree structure representing the clustering process more detailed from the root node to the leaf node. In which the root node and intermediate nodes act as the orientation for data distribution, and the leaf nodes represent real clusters of data. This training tree structure allows programming parallel processing to speed up network training. In addition, applying the trained network could be more efficient because the search process performed on the tree structure.
Copyright © 2012–2024 ICST
