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Frontiers of Computer Science

Front. Comput. Sci.    2018, Vol. 12 Issue (5) : 1032-1034
Center-based clustering of categorical data using kernel smoothing methods
Xuanhui YAN, Lifei CHEN(), Gongde GUO
School of Mathematics and Informatics, Fujian Normal University, Fuzhou 350007, China
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Corresponding Authors: Lifei CHEN   
Online First Date: 04 September 2018    Issue Date: 21 September 2018
 Cite this article:   
Xuanhui YAN,Lifei CHEN,Gongde GUO. Center-based clustering of categorical data using kernel smoothing methods[J]. Front. Comput. Sci., 2018, 12(5): 1032-1034.
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Xuanhui YAN
Lifei CHEN
Gongde GUO
1 Jain A K, Murty M N, Flynn P J. Data clustering: a review. ACM Computing Survey, 1999, 31(3): 264–323
2 Jing L, Ng M K, Huang J Z. An entropy weighting K-means algorithm for subspace clustering of high-dimensinoal sparse data. IEEE Transactions on Knowledge and Data Engineering, 2007, 19(8): 1–16
3 Sun H, Wang S, Jiang Q. FCM-based model selection algorithms for determining the number of clusters. Pattern Recognition, 2004, 37(10): 2027–2037
4 Ouyang D, Li Q, Racine J. Cross-validation and the estimation of probability distributions with categorical data. Nonparametric Statistics, 2006, 18(1): 69–100
5 Bai L, Liang J, Dang C, Cao F. A novel attribute weighting algorithm for clustering high-dimensional categorical data. Pattern Recognition, 2011, 44(12): 2843–2861
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