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A semi-supervised approximate spectral clustering algorithm based on HMRF model
Ding, Shifei1,2; Jia, Hongjie1,3; Du, Mingjing1,2; Xue, Yu4
2018-03-01
发表期刊INFORMATION SCIENCES
ISSN0020-0255
卷号429页码:215-228
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.
关键词Semi-supervised learning Spectral clustering HMRF model Approximate weighted kernel k-means Matrix trace
DOI10.1016/j.ins.2017.11.016
收录类别SCI
语种英语
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
WOS类目Computer Science, Information Systems
WOS记录号WOS:000423653300015
出版者ELSEVIER SCIENCE INC
引用统计
被引频次:45[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://119.78.100.204/handle/2XEOYT63/5619
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.China Univ Min & Technol, Sch Comp Sci & Technol, Xuzhou 221116, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100090, Peoples R China
3.Jiangsu Univ, Sch Comp Sci & Commun Engn, Zhenjiang 212013, Peoples R China
4.Nanjing Univ Informat Sci & Technol, Sch Comp & Software, Nanjing 210044, Jiangsu, Peoples R China
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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.
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