Title

Recent Advances in Cluster Analysis

Abstract

Purpose
The purpose of this paper is to provide a review of the issues related to cluster analysis, one of the most important and primitive activities of human beings, and of the advances made in recent years.
Design/methodology/approach
The paper investigates the clustering algorithms rooted in machine learning, computer science, statistics, and computational intelligence.
Findings
The paper reviews the basic issues of cluster analysis and discusses the recent advances of clustering algorithms in scalability, robustness, visualization, irregular cluster shape detection, and so on.
Originality/value
The paper presents a comprehensive and systematic survey of cluster analysis and emphasizes its recent efforts in order to meet the challenges caused by the glut of complicated data from a wide variety of communities.

Department(s)

Electrical and Computer Engineering

International Standard Serial Number (ISSN)

1756-378X

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2008 Emerald, All rights reserved.


Share

 
COinS