Article thumbnail

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

By Lee Chang Wui, Meng Tay Kai and Peng Lim Chee

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 problem

Topics: QA75 Electronic computers. Computer science
Year: 2013
OAI identifier: oai:ir.unimas.my:15839
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://ir.unimas.my/id/eprint/... (external link)
  • http://ir.unimas.my/id/eprint/... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.