Page 189 - 《软件学报》2020年第11期
P. 189

徐鲲鹏  等:类属型数据核子空间聚类算法                                                            3505


                [16]     Hartigan J A, Wong MA. A K-means clustering algorithm. Applied Statistics, 1979,28(1):100−108. [doi: 10.2307/2346830]
                [17]    Sun H, Wang S, Jiang Q. FCM-based model selection algorithms for determining the number of clusters. Pattern Recognition, 2004,
                     37(10):2027−2037. [doi: 10.1016/j.patcog.2004.03.012]
                [18]     Burnham KP, Anderson DR. Model Selection and Multimodel Inference: A Practical Information-theoretic Approach. Springer-
                     Verlag, 2002. [doi: 10.1198/tech.2003.s146]
                [19]     Pelleg D, Moore AW. X-means: Extending K-means with efficient estimation of the number of clusters. In: Proc. of the 17th Int’l
                     Conf. on Machine Learning. 2000. [doi: 10.1007/3-540-44491-2_3]
                [20]     Bai L, Liang  J, Dang  C,  et  al.  A novel  attribute weighting  algorithm for  clustering high-dimensional  categorical data. Pattern
                     Recognition, 2011,44(12):2843−2861. [doi: 10.1016/j.patcog.2011.04.024]
                [21]     Chen L, Jiang Q, Wang S. A probability model for projective clustering on high dimensional data. In: Proc. of the IEEE Int’l Conf.
                     on Data Mining. 2008. 755−760. [doi: 10.1109/ICDM.2008.15]
                [22]     Chen LF. A  probabilistic  framework  for  optimizing projected clusters with categorical attributes.  Science China Information
                     Sciences, 2015,58(7):1−15. [doi: 10.1007/s11432-014-5267-5]
                [23]     Bezdek JC. Pattern Analysis in Handbook of Fuzzy Computation. IOP Publishing Ltd., 1998. [doi: 10.1887/0750304278]

                 附中文参考文献:
                  [1]  韩家炜,Kamber M,裴健,著;范明,孟小峰,译.数据挖掘:概念与技术.第 3 版,北京:机械工业出版社,2012. [doi: 10.3969/j.issn.1674-
                     6511.2008.03.043]
                  [2]  陈黎飞,吴涛.数据挖掘中的特征约简.北京:科学出版社,2016.
                  [3]  蔡晓妍,戴冠中,杨黎斌.谱聚类算法综述.计算机科学,2008,35(7):14−18. [doi: 10.3969/j.issn.1002-137X.2008.07.004]
                  [7]  陈黎飞,郭躬德,姜青山.自适应的软子空间聚类算法.软件学报,2010,21(10):2513−2523. http://www.jos.org.cn/1000-9825/3763.
                     htm [doi: 10.3724/SP.J.1001.2010.03763]
                 [11]  孔锐,张国宣,施泽生,等.基于核的 K-均值聚类.计算机工程,2004,30(11):12−13,80. [doi: 10.3969/j.issn.1000-3428.2004.11.005]



                              徐鲲鹏(1994－),男,硕士,主要研究领域为                      孙浩军(1963－),男,博士,教授,CCF 专业
                              数据挖掘,模式识别,机器学习.                              会员,主要研究领域为数据挖掘,模式识
                                                                           别,信息系统.



                              陈黎飞(1972－),男,博士,教授,博士生导                      王备战(1965－),男,博士,教授,博士生导
                              师,主要研究领域为数据挖掘,模式识别,                          师,CCF 专业会员,主要研究领域为数据挖
                              机器学习.                                        掘,数据库与数据仓库,软件体系结构.
   184   185   186   187   188   189   190   191   192   193   194