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基于图划分的网状高阶异构数据联合聚类算法 被引量：1

A Net-structure High-order Heterogeneous Data Co-clustering Algorithm Based on Graph Partitioning
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摘要 目前已有的高阶联合聚类算法主要集中于分析星型高阶异构数据,然而实际应用中,存在大量网状高阶异构数据。为了有效挖掘网状高阶异构数据内部隐藏的结构,提出一种基于图划分的高阶联合聚类算法(简称为GPHCC),该算法将网状高阶异构数据的聚类问题转化为多对二部图的最小正则割划分问题。为了降低计算复杂度,将此优化问题转化为半正定问题求解。实验结果表明GPHCC算法优于目前已有的5种2阶联合聚类算法和5种高阶联合聚类算法。 Existing high-order co-clustering algorithm just can be suitable for analyzing star-structure high-order heterogeneous data. In order to analyze net-structure high-order heterogeneous data, a high-order co-clustering algorithm based on graph partitioning was pro- posed. The problem of high-order co-clustering was converted to optimal problem of graph partitioning of minimum normal cut. In order to reduce computational complexity, the optimal problem was converted to semi-definite problem. Experimental studies showed that the qualities of clustering results of GPHCC are superior five pair-wise coclustering algorithms and five high-order co-clustering algorithms.
作者 杨欣欣 黄少滨
机构地区 哈尔滨工程大学计算机科学与技术学院
出处 《四川大学学报（工程科学版）》 EI CAS CSCD 北大核心 2014年第2期105-110,共6页 Journal of Sichuan University (Engineering Science Edition)
基金 国家自然科学基金资助项目(71272216 60903080 60093009) 博士后科学基金资助项目(2012M5100480) 国家科技支撑计划资助项目(2009BAH42B02 2012BAH08B02) 中央高校基本科研业务费专项基金资助项目(HEUCFZ1212 HEUCFT1208)
关键词 网状结构 高阶异构数据 联合聚类 谱聚类 net-structure high-order heterogeneous data co-clustering spectral clustering
分类号 TP181 [自动化与计算机技术—控制理论与控制工程]
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参考文献21

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同被引文献14

  • 1许宁,张毅坤.基于正交分层聚类算法软件可靠性模型的预测分析[J].计算机应用,2007,27(3):635-637. 被引量：6
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  • 5FU L,NIU B,ZHU Z, et al. CD-HIT: accelerated forclustering the next-generation sequencing data [ J ]. Bioin-formatics, 2012, 28(23) : 3150-3152.
  • 6TIAN Zheng, LI Xiaobin, JU Yanwei. Disturbing Analy-sis on Spectrum Clustering[ J]. Science in China: SeriesE, 2007,37(4) : 527-543.
  • 7JAIN A K. Data clustering : 50 years beyond K-means [ J ].Pattern Recognition Letters, 2010, 31(8) : 651-666.
  • 8DOMINGOS P. Prospects and challenges for multi-rela-tional data mining[J]. ACM SIGKDD Explorations News-letter, 2003,5(1) : 80-83.
  • 9张薇,刘加.电话语音的多说话人分割聚类研究[J].清华大学学报（自然科学版）,2008,48(4):574-577. 被引量：6
  • 10马素琴,施化吉.阈值优化的文本密度聚类算法[J].计算机工程与应用,2011,47(17):134-136. 被引量：6

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四川大学学报（工程科学版）
2014年 第2期

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