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Reseach Article

Knowledge Assisted Visualization for Imbalanced Data Clustering

Published on February 2013 by P. Alagambigai, K. Thangavel
International Conference on Communication, Computing and Information Technology
Foundation of Computer Science USA
ICCCMIT - Number 2
February 2013
Authors: P. Alagambigai, K. Thangavel
dcf07ed7-74c5-4ecd-98cd-38faef0a3b05

P. Alagambigai, K. Thangavel . Knowledge Assisted Visualization for Imbalanced Data Clustering. International Conference on Communication, Computing and Information Technology. ICCCMIT, 2 (February 2013), 6-13.

@article{
author = { P. Alagambigai, K. Thangavel },
title = { Knowledge Assisted Visualization for Imbalanced Data Clustering },
journal = { International Conference on Communication, Computing and Information Technology },
issue_date = { February 2013 },
volume = { ICCCMIT },
number = { 2 },
month = { February },
year = { 2013 },
issn = 0975-8887,
pages = { 6-13 },
numpages = 8,
url = { /specialissues/icccmit/number2/10330-1014/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 International Conference on Communication, Computing and Information Technology
%A P. Alagambigai
%A K. Thangavel
%T Knowledge Assisted Visualization for Imbalanced Data Clustering
%J International Conference on Communication, Computing and Information Technology
%@ 0975-8887
%V ICCCMIT
%N 2
%P 6-13
%D 2013
%I International Journal of Computer Applications
Abstract

The common challenge which is faced by much of the data clustering techniques is data complexity, which leads to many issues such as overlapping, lack of representative data and class imbalance. This may deteriorates the clustering process. The situation gets worse when the class imbalance is very high. To cluster such imbalanced data sets, better understandings of the dataset and efficient clustering algorithms are required. This could be achieved by integrating suitable domain intelligence into the clustering process. In this paper, Knowledge Assisted Visualization framework is proposed for imbalanced data clustering and validation. The proposed Knowledge Assisted Visualization framework integrates an efficient visual clustering framework with suitable domain intelligence acquired from domain experts and users into clustering process. An experimental analysis is carried out over a wide range of highly imbalanced data sets. Experiments demonstrate that the proposed method works well with imbalanced dataset and eases the cluster identification and validation in an effective way.

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Index Terms

Computer Science
Information Sciences

Keywords

Data Mining Class Imbalance Interactive Clustering Knowledge Assisted Visualization Visual Clustering