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一种基于信任值的分类属性聚类算法

A categorical attribute clustering algorithm based on trust value
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摘要 针对K-Modes算法的不足,提出了一种基于信任值的分类属性聚类算法TrustCCluster,该算法不需预先给定聚类个数,聚类结果稳定且不依赖于初始值的选取。在真实数据上验证了TrustC-Cluster聚类算法,并与K-Modes和P-Modes算法进行了对比,实验结果表明TrustCCluster算法是有效、可行的。 For the shortage of K-Modes algorithm, a categorical attribute clustering algorithm TrustCCluster based on trust val-ue is proposed, the algorithm does not need to pre-specify the number of clusters, and clustering results do not depend on the se-lection of the initial values. TrustCCluster clustering algorithm is verified on the real data, and compared with the K-Mode and P-Modes algorithms, the result shows that TrustCCluster algorithm is feasible and effective.
作者 李梓 蒋庆丰 程晓旭 贾美娟
机构地区 大庆师范学院计算机科学与技术学院
出处 《微型机与应用》 2012年第22期57-59,63,共4页 Microcomputer & Its Applications
基金 黑龙江省自然科学基金项目(F200923) 黑龙江省教育厅科学技术研究项目(11553001)
关键词 信任值 聚类 K—Modes算法 P—Modes算法 trust value cluster K-Modes algorithm P-Modes algorithm
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
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参考文献8

  • 1MACQUEEN J.Some methods for classification and analysis of multivariate observations[C].Proc 5th Berkeley Symposium Mathematics Statist and Probaility, 1967:281-297.
  • 2KAUFMAN J, ROUSSEEUW P J.Finding groups in data: an introduction to cluster analysis[M].New York :John Wiley&Sons, 1990.
  • 3ESTER M, KRIEGEL H P, SANDER J, et al.A density- based algorithm for discovering clusters in large spatial databases [C]. Proc. of 1996 Intl. Conf. on Knowledge Discovery and Data Mining,Portland,OR.1996:226-231.
  • 4WANG W, YANG J, MUNTZ R.STING : A statistical information grid approach to spatial data mining[C].Proc of 1997 Intl.Conf.on Very Large Databases, Athens, Greece. 1997 : 186-195.
  • 5KOHONEN T.Self-organized formation of topologically correct feature maps [J]. Biological Cybernetics, 1982,43 (1) :59-69.
  • 6Huang Zhexue.Clustering large data sets with mixed numeric and categorical values[C].Proc of PAKDD 97.Singapore: World Scientific, 1997 : 21-35.
  • 7Huang Zhexue.Extensions to the K-means algorithm for clustering large data sets with categorical values[J].Data Mining and Knowledge Discovery, 1998,2(3) : 283-304.
  • 8梁吉业,白亮,曹付元.基于新的距离度量的K-Modes聚类算法[J].计算机研究与发展,2010,47(10):1749-1755. 被引量：46

二级参考文献26

  • 1陈宗海,文锋,聂建斌,吴晓曙.基于节点生长k-均值聚类算法的强化学习方法[J].计算机研究与发展,2006,43(4):661-666. 被引量：13
  • 2Han Jiawei,Kamber M.Data Mining Concepts and Techniques[M].San Francisco:Morgan Kaufmann,2001.
  • 3Brendan J F,Delbert D.Clustering by passing messages between data points[J].Science,2007,315(16):972-976.
  • 4Zhang Jiangshe,Liang Yiuwing.Improved possibilistic c-means clustering algorithms[J].IEEE Trans on Fuzzy Systems,2004,12(2):209-217.
  • 5Mac Q J.Some methods for classification and analysis of multivariate observation[C]//Proc of the 5th Berkley Symp on Mathematical Statistics and Probability.Berkley,California:University of California Press,1967:281-297.
  • 6Huang Zhexue.Clustering large data sets with mixed numeric and categorical values[C]//Proc of PAKDD97.Singapore:World Scientific,1997:21-35.
  • 7Huang Zhexue.Extensions to the K-means algorithm for clustering large data sets with categorical values[J].Data Mining and Knowledge Discovery,1998,2(3):283-304.
  • 8Ng M K,Li Junjie,Huang Zhexue,et al.On the impact of dissimilarity measure in K-modes clustering algorithm[J].IEEE Trans on Pattern Analysis and Machine Intelligence,2007,29(3):503-507.
  • 9San O M,Huynh V N,Nakamori Y.An alternative extension of the K-means algorithm for clustering categorical data[J].Int Journal Application Mathematic and Computer Science,2004,14(2):241-247.
  • 10Li Cen,Biswas G.Unsupervised learning with mixed numeric and nominal data[J].IEEE Trans on Knowledge and Data Engineering,2002,14(4):673-690.

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微型机与应用
2012年 第22期

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