Self-Tuning p-Spectral Clustering Based on Shared Nearest Neighbors

doi:10.1007/s12559-015-9331-2

	Self-Tuning p-Spectral Clustering Based on Shared Nearest Neighbors
	Jia, Hongjie 1,2; Ding, Shifei 1,2; Du, Mingjing 1,2
	2015-10-01
发表期刊	COGNITIVE COMPUTATION
ISSN	1866-9956
卷号	7 期号:5 页码:622-632
摘要	Cognitive computing needs to handle large amounts of data and information. Spectral clustering is a powerful data mining tool based on algebraic graph theory. Because of the solid theoretical foundation and good clustering performance, spectral clustering has aroused extensive attention of academia in recent years. Spectral clustering transforms the data clustering problem into the graph partitioning problem. Cheeger cut is an optimized graph partitioning criterion. To minimize the objective function of Cheeger cut, the eigen-decomposition of p-Laplacian matrix is required. However, the clustering results are sensitive to the selection of similarity measurement and the parameter p of p-Laplacian matrix. Therefore, we propose a self-tuning p-spectral clustering algorithm based on shared nearest neighbors (SNN-PSC). This algorithm uses shared nearest neighbors to measure the similarities of data couples and then applies fruit fly optimization algorithm to find the optimal parameters p of p-Laplacian matrix that leads to better data classification. Experiments show that SNN-PSC algorithm can produce more balanced clusters and has strong adaptability and robustness compared to traditional spectral clustering algorithms.
关键词	Spectral clustering Cheeger cut p-Laplacian SNN FOA
DOI	10.1007/s12559-015-9331-2
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61379101] ; National Key Basic Research Program of China[2013CB329502]
WOS研究方向	Computer Science ; Neurosciences & Neurology
WOS类目	Computer Science, Artificial Intelligence ; Neurosciences
WOS记录号	WOS:000360995300010
出版者	SPRINGER
引用统计	被引频次：26[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/2XEOYT63/9380
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 100190, Peoples R China
推荐引用方式 GB/T 7714	Jia, Hongjie,Ding, Shifei,Du, Mingjing. Self-Tuning p-Spectral Clustering Based on Shared Nearest Neighbors[J]. COGNITIVE COMPUTATION,2015,7(5):622-632.
APA	Jia, Hongjie,Ding, Shifei,&Du, Mingjing.(2015).Self-Tuning p-Spectral Clustering Based on Shared Nearest Neighbors.COGNITIVE COMPUTATION,7(5),622-632.
MLA	Jia, Hongjie,et al."Self-Tuning p-Spectral Clustering Based on Shared Nearest Neighbors".COGNITIVE COMPUTATION 7.5(2015):622-632.