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Enhancing an evolving tree-based text document visualization model with fuzzy c-means clustering

An improved evolving model, i.e., Evolving Tree (ETree) with Fuzzy c-Means (FCM), is proposed for undertaking text document visualization problems in this study. ETree forms a hierarchical tree structure in which nodes (i.e., trunks) are allowed to grow and split into child nodes (i.e., leaves), and...

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Main Authors: Wui, Lee Chang, Kai, Meng Tay, Chee, Peng Lim
Format: Conference or Workshop Item
Language:English
Published: 2013
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://ir.unimas.my/id/eprint/15839/1/Enhancing%20an%20evolving%20tree-based%20text%20document%20visualization%20model%20with%20fuzzy%20c-means%20clustering%20%28abstrak%29.pdf
http://ir.unimas.my/id/eprint/15839/
http://ieeexplore.ieee.org/document/6622363/
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spelling my.unimas.ir.158392017-05-02T02:48:34Z http://ir.unimas.my/id/eprint/15839/ Enhancing an evolving tree-based text document visualization model with fuzzy c-means clustering Wui, Lee Chang Kai, Meng Tay Chee, Peng Lim QA75 Electronic computers. Computer science An improved evolving model, i.e., Evolving Tree (ETree) with Fuzzy c-Means (FCM), is proposed for undertaking text document visualization problems in this study. ETree forms a hierarchical tree structure in which nodes (i.e., trunks) are allowed to grow and split into child nodes (i.e., leaves), and each node represents a cluster of documents. However, ETree adopts a relatively simple approach to split its nodes. Thus, FCM is adopted as an alternative to perform node splitting in ETree. An experimental study using articles from a flagship conference of Universiti Malaysia Sarawak (UNIMAS), i.e., Engineering Conference (ENCON), is conducted. The experimental results are analyzed and discussed, and the outcome shows that the proposed ETree-FCM model is effective for undertaking text document clustering and visualization problems 2013 Conference or Workshop Item PeerReviewed text en http://ir.unimas.my/id/eprint/15839/1/Enhancing%20an%20evolving%20tree-based%20text%20document%20visualization%20model%20with%20fuzzy%20c-means%20clustering%20%28abstrak%29.pdf Wui, Lee Chang and Kai, Meng Tay and Chee, Peng Lim (2013) Enhancing an evolving tree-based text document visualization model with fuzzy c-means clustering. In: 2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013, 7 July 2013 through 10 July 2013, Hyderabad; India;. http://ieeexplore.ieee.org/document/6622363/
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Wui, Lee Chang
Kai, Meng Tay
Chee, Peng Lim
Enhancing an evolving tree-based text document visualization model with fuzzy c-means clustering
description An improved evolving model, i.e., Evolving Tree (ETree) with Fuzzy c-Means (FCM), is proposed for undertaking text document visualization problems in this study. ETree forms a hierarchical tree structure in which nodes (i.e., trunks) are allowed to grow and split into child nodes (i.e., leaves), and each node represents a cluster of documents. However, ETree adopts a relatively simple approach to split its nodes. Thus, FCM is adopted as an alternative to perform node splitting in ETree. An experimental study using articles from a flagship conference of Universiti Malaysia Sarawak (UNIMAS), i.e., Engineering Conference (ENCON), is conducted. The experimental results are analyzed and discussed, and the outcome shows that the proposed ETree-FCM model is effective for undertaking text document clustering and visualization problems
format Conference or Workshop Item
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
title Enhancing an evolving tree-based text document visualization model with fuzzy c-means clustering
title_short Enhancing an evolving tree-based text document visualization model with fuzzy c-means clustering
title_full Enhancing an evolving tree-based text document visualization model with fuzzy c-means clustering
title_fullStr Enhancing an evolving tree-based text document visualization model with fuzzy c-means clustering
title_full_unstemmed Enhancing an evolving tree-based text document visualization model with fuzzy c-means clustering
title_sort enhancing an evolving tree-based text document visualization model with fuzzy c-means clustering
publishDate 2013
url http://ir.unimas.my/id/eprint/15839/1/Enhancing%20an%20evolving%20tree-based%20text%20document%20visualization%20model%20with%20fuzzy%20c-means%20clustering%20%28abstrak%29.pdf
http://ir.unimas.my/id/eprint/15839/
http://ieeexplore.ieee.org/document/6622363/
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score 13.244404

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