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

conference contribution
posted on 2013-01-01, 00:00 authored by W Chang, K Tay, Chee Peng LimChee Peng Lim
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.

History

Event

Fuzzy Systems. IEEE International Conference (2013 : Hyderabad, India)

Pagination

1 - 6

Publisher

IEEE

Location

Hyderabad, India

Place of publication

Piscataway, N.J.

Start date

2013-07-07

End date

2013-07-10

Language

eng

Publication classification

E1 Full written paper - refereed

Copyright notice

2013, IEEE

Title of proceedings

FUZZ-IEEE 2013 : Proceedings of the IEEE International Conference on Fuzzy Systems