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一种有效的高属性维稀疏数据聚类算法*

, PP. 289-294

Keywords: 稀疏相似度,等价关系的相似度,数据压缩,聚类

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Abstract:

聚类分析是数据挖掘最常见的技术之一,数据的规模、维数和稀疏性都是制约聚类分析的不同方面.本文提出一种有效的高属性维稀疏数据聚类方法.给出稀疏相似度、等价关系的相似度、广义的等价关系的定义.基于对象间的稀疏相似度和等价关系原理形成初始等价类,通过等价关系的相似度修正初始等价关系,使得最终聚类结果更合理.该算法聚类过程不依赖于输入样本的排列顺序,高维稀疏数据的有效压缩提高算法在维数较高时的执行效率,适合于高维稀疏数据的聚类分析.

References

[1]  Han J, Kamber M. Data Mining: Concepts and Techniques. New York, USA: Morgan Kaufmann, 2001 (Han J, Kamber M,著;范 明, 孟小峰, 等,译. 数据挖掘概念与技术. 北京: 机械工业出版社, 2001)
[2]  Bradley P S, Fayyad U M, Reina C. Scaling Clustering Algorithms to Large Databases. In: Proc of the 4th International Conference on Knowledge Discovery and Data Mining. Menlo Park, USA, 1998, 9-15
[3]  Wu S, Gao X D, et al. Knowledge Discovery for High Dimension Sparse Clustering. Beijing, China: Metallurgical Industry Press, 2003 (in Chinese) (武 森, 高学东,等. 高维稀疏聚类知识发现. 北京: 冶金工业出版社, 2003)
[4]  Hirano S, Tsumoto S, Okuzaki T, Hata Y. A Clustering Method for Nominal and Numerical Data Based on Rough Set Theory. In: Proc of the International Workshop on Rough Set Theory and Granular Computing. Matsue, Japan, 2001, 211-216
[5]  Miao D Q, Wang J. An Information Representation of the Concepts and Operations in Rough Set Theory. Journal of Software, 1999, 10(2): 113-116 (in Chinese) (苗夺谦, 王 珏. 粗糙集理论中概念与运算的信息表示. 软件学报, 1999, 10(2): 113-116)
[6]  Zhou Y Q, Jiao L C. High Attribute Dimensional Sparse Clustering Recurrent Logical Neural Networks Model and Learning Algorithm. Acta Electronica Sinica, 2004, 32(8): 1342-1345 (in Chinese) (周永权, 焦李成. 高属性维稀疏数据聚类回归逻辑神经网络模型及学习算法. 电子学报, 2004, 32(8): 1342-1345)
[7]  An Q S, Shen J Y, Wang G Y. A Clustering Method Based on Information Granularity and Rough Sets. Pattern Recognition and Artificial Intelligence, 2003, 16(4): 412-417 (in Chinese) (安秋生, 沈钧毅, 王国胤. 基于信息粒度与Rough集的聚类方法研究. 模式识别与人工智能, 2003, 16(4): 412-417)
[8]  Hirano S, Tsumoto S. Dealing with Relatively Proximity by Rough Clustering. In: Proc of the 22nd International Conference of the North American Fuzzy Information Processing Society. Chicago, USA, 2003, 260-265

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