Clustering based on sequential representation of minimum spanning tree

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

This paper aims to solve three types of clustering problems (i.e., well-separated, relaxed well separated and connected ones) based on minimum spanning tree (MST) technique. Through analyzing the characteristics of each clustering problem, a good property of inconsistent edges is found and reformulated with several theorems based on the sequential representation of MST. Meanwhile, a new MST-based clustering algorithm SR-MSTC is proposed with purpose to reduce computational cost and to overcome the mutual influence of inconsistent edges. Some experiments demonstrate that SR-MSTC works well to identify different types of clusters embodied in the given data while having lower computational complexity.

Original languageEnglish
Title of host publicationProceedings of 2011 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR 2011
Pages132-137
Number of pages6
DOIs
StatePublished - 2011
Event2011 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR 2011 - Guilin, Guangxi, China
Duration: 10 Jul 201113 Jul 2011

Publication series

NameInternational Conference on Wavelet Analysis and Pattern Recognition
ISSN (Print)2158-5695
ISSN (Electronic)2158-5709

Conference

Conference2011 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR 2011
Country/TerritoryChina
CityGuilin, Guangxi
Period10/07/1113/07/11

Keywords

  • Clustering
  • Minimum spanning tree
  • Prim's algorithm

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