A semi-supervised approximate spectral clustering algorithm based on HMRF model

doi:10.1016/j.ins.2017.11.016

CORC > 计算技术研究所 > 中国科学院计算技术研究所 > 中国科学院计算技术研究所期刊论文 > 英文

	A semi-supervised approximate spectral clustering algorithm based on HMRF model
	Ding, Shifei 3,4; Jia, Hongjie 1,4; Du, Mingjing 3,4; Xue, Yu 2
刊名	INFORMATION SCIENCES
	2018-03-01
卷号	429 页码:215-228
关键词	Semi-supervised learning Spectral clustering HMRF model Approximate weighted kernel k-means Matrix trace
ISSN号	0020-0255
DOI	10.1016/j.ins.2017.11.016
英文摘要	Before clustering, we usually have some background knowledge about the data structure. Pairwise constraints are commonly used background knowledge. For graph partition problems, pairwise constraints can be naturally added to the graph edge. This paper integrates pairwise constraints into the objective function of graph cuts and derive the semi-supervised approximate spectral clustering based on Hidden Markov Random Fields (HMRF). This algorithm utilize the mathematical connection between HMRF semi-supervised clustering and approximate weighted kernel k-means. The approximate weighted kernel k-means is used to calculate the optimal clustering results of HMRF spectral clustering. The effectiveness of the proposed algorithm is verified on several benchmark data sets. Experiments show that adding more pairwise constraints will help improve the clustering performance. Our method has advantages for the challenging clustering tasks of large-scale nonlinear data because of the high efficiency and less memory consumption. (C) 2017 Elsevier Inc. All rights reserved.
资助项目	National Natural Science Foundations of China[61672522] ; National Natural Science Foundations of China[61379101] ; National Key Basic Research Program of China[2013CB329502] ; Priority Academic Program Development of Jiangsu Higer Education Institutions (PAPD) ; Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology(CICAEET)
WOS研究方向	Computer Science
语种	英语
出版者	ELSEVIER SCIENCE INC
WOS记录号	WOS:000423653300015
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/5618]
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Ding, Shifei
作者单位	1.Jiangsu Univ, Sch Comp Sci & Commun Engn, Zhenjiang 212013, Peoples R China 2.Nanjing Univ Informat Sci & Technol, Sch Comp & Software, Nanjing 210044, Jiangsu, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100090, Peoples R China 4.China Univ Min & Technol, Sch Comp Sci & Technol, Xuzhou 221116, Peoples R China
推荐引用方式 GB/T 7714	Ding, Shifei,Jia, Hongjie,Du, Mingjing,et al. A semi-supervised approximate spectral clustering algorithm based on HMRF model[J]. INFORMATION SCIENCES,2018,429:215-228.
APA	Ding, Shifei,Jia, Hongjie,Du, Mingjing,&Xue, Yu.(2018).A semi-supervised approximate spectral clustering algorithm based on HMRF model.INFORMATION SCIENCES,429,215-228.
MLA	Ding, Shifei,et al."A semi-supervised approximate spectral clustering algorithm based on HMRF model".INFORMATION SCIENCES 429(2018):215-228.