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

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;.

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Official URL: http://ieeexplore.ieee.org/document/6622363/

Abstract

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

Item Type: Proceeding (Paper)
Uncontrolled Keywords: unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, research, Universiti Malaysia Sarawak, Evolving tree; Fuzzy c-means; Online learning; Text document clustering; Visualization
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Academic Faculties, Institutes and Centres > Faculty of Engineering
Depositing User: Saman
Date Deposited: 05 Apr 2017 07:48
Last Modified: 02 May 2017 02:48
URI: http://ir.unimas.my/id/eprint/15839

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