A New Evolving Tree for Text Document Clustering and Visualization
The Self-Organizing Map (SOM) is a popular neural network model for clustering and visualization problems. However, it suffers from two major limitations, viz., (1) it does not support online learning; and (2) the map size has to be pre-determined and this can potentially lead to many “trial-and-err...
| Main Authors: | , , |
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| Format: | Book Chapter |
| Published: |
Springer International Publishing
2013
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| Online Access: | http://ir.unimas.my/id/eprint/5237/ |
| _version_ | 1848835615079006208 |
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| author | Wui, Lee Chang Kai, Meng Tay Chee, Peng Lim |
| author_facet | Wui, Lee Chang Kai, Meng Tay Chee, Peng Lim |
| author_sort | Wui, Lee Chang |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | The Self-Organizing Map (SOM) is a popular neural network model for clustering and visualization problems. However, it suffers from two major limitations, viz., (1) it does not support online learning; and (2) the map size has to be pre-determined and this can potentially lead to many “trial-and-error” runs before arriving at an optimal map size. Thus, an evolving model, i.e., the Evolving Tree (ETree), is used as an alternative to the SOM for undertaking a text document clustering problem in this study. ETree forms a hierarchical (tree) structure in which nodes are allowed to grow, and each leaf node represents a cluster of documents. An experimental study using articles from a flagship conference of Universiti Malaysia Sarawak (UNIMAS), i.e., the Engineering Conference (ENCON), is conducted. The experimental results are analyzed and discussed, and the outcome shows a new application of ETree in text document clustering and visualization. |
| first_indexed | 2025-11-15T06:10:41Z |
| format | Book Chapter |
| id | unimas-5237 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| last_indexed | 2025-11-15T06:10:41Z |
| publishDate | 2013 |
| publisher | Springer International Publishing |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-52372015-07-27T06:46:38Z http://ir.unimas.my/id/eprint/5237/ A New Evolving Tree for Text Document Clustering and Visualization Wui, Lee Chang Kai, Meng Tay Chee, Peng Lim T Technology (General) The Self-Organizing Map (SOM) is a popular neural network model for clustering and visualization problems. However, it suffers from two major limitations, viz., (1) it does not support online learning; and (2) the map size has to be pre-determined and this can potentially lead to many “trial-and-error” runs before arriving at an optimal map size. Thus, an evolving model, i.e., the Evolving Tree (ETree), is used as an alternative to the SOM for undertaking a text document clustering problem in this study. ETree forms a hierarchical (tree) structure in which nodes are allowed to grow, and each leaf node represents a cluster of documents. An experimental study using articles from a flagship conference of Universiti Malaysia Sarawak (UNIMAS), i.e., the Engineering Conference (ENCON), is conducted. The experimental results are analyzed and discussed, and the outcome shows a new application of ETree in text document clustering and visualization. Springer International Publishing 2013 Book Chapter PeerReviewed Wui, Lee Chang and Kai, Meng Tay and Chee, Peng Lim (2013) A New Evolving Tree for Text Document Clustering and Visualization. In: A New Evolving Tree for Text Document Clustering and Visualization. Advances in Intelligent Systems and Computing . Springer International Publishing, pp. 141-151. ISBN 978-3-319-00930-8 http://link.springer.com/chapter/10.1007%2F978-3-319-00930-8_13 |
| spellingShingle | T Technology (General) Wui, Lee Chang Kai, Meng Tay Chee, Peng Lim A New Evolving Tree for Text Document Clustering and Visualization |
| title | A New Evolving Tree for Text Document Clustering and Visualization |
| title_full | A New Evolving Tree for Text Document Clustering and Visualization |
| title_fullStr | A New Evolving Tree for Text Document Clustering and Visualization |
| title_full_unstemmed | A New Evolving Tree for Text Document Clustering and Visualization |
| title_short | A New Evolving Tree for Text Document Clustering and Visualization |
| title_sort | new evolving tree for text document clustering and visualization |
| topic | T Technology (General) |
| url | http://ir.unimas.my/id/eprint/5237/ http://ir.unimas.my/id/eprint/5237/ |