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Locally incremental visual cluster analysis using Markov random field
Zhou, Zhen; Zhong, Li; Wang, Liang
Source PublicationNEUROCOMPUTING
2014-07-20
Volume136Issue:136Pages:49-55
SubtypeArticle
AbstractClustering methods are widely deployed in the fields of data mining and pattern recognition. Many of them require the number of clusters as the input, which may not be practical when it is totally unknown. Several existing visual methods for cluster tendency assessment can be used to estimate the number of clusters by displaying the pairwise dissimilarity matrix into an intensity image where objects are reordered to reveal the hidden data structure as dark blocks along the diagonal. A major limitation of the existing methods is that they are not capable to highlight cluster structure with complex clusters. To address this problem, this paper proposes an effective approach by using Markov Random Fields, which updates each object with its local information dynamically and maximizes the global probability measure. The proposed method can be used to determine the cluster tendency and partition data simultaneously. Experimental results on synthetic and real-world datasets demonstrate the effectiveness of the proposed method. (C) 2014 Elsevier B.V. All rights reserved.
KeywordVisual Cluster Analysis Markov Random Field Visual Assessment Tendency
WOS HeadingsScience & Technology ; Technology
WOS KeywordLARGE DATA SETS ; TENDENCY ASSESSMENT ; NUMBER
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000335708800006
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/3811
Collection智能感知与计算研究中心
AffiliationChinese Acad Sci, Ctr Res Intelligent Percept & Comp, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Zhou, Zhen,Zhong, Li,Wang, Liang. Locally incremental visual cluster analysis using Markov random field[J]. NEUROCOMPUTING,2014,136(136):49-55.
APA Zhou, Zhen,Zhong, Li,&Wang, Liang.(2014).Locally incremental visual cluster analysis using Markov random field.NEUROCOMPUTING,136(136),49-55.
MLA Zhou, Zhen,et al."Locally incremental visual cluster analysis using Markov random field".NEUROCOMPUTING 136.136(2014):49-55.
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