参考文献
[1]Chen Dongming,Yan Yun,Wang Dongqi.Density Clustering Based on Border-expanding[C]//Proceed-ings of the 10th International Conference on Natural Computation.Washington D.C.,USA:IEEE Press,2014:670-674.
[2]Ye Zonglin,Cao Hui,Jia Lixin,et al.Multi-radius Density Clustering Algorithm Based on Outlier Factor[J].Applied Mechanics & Materials,2014,472:427-431.
[3]Chen Qi,Lu Jianfeng,Zhang Hao.A Text Mining Model Based on Improved Density Clustering Algorithm[C]//Proceedings of the 4th International Conference on
Electronics Information and Emergency Communication.Washington D.C.,USA:IEEE Press,2013:337-339.
[4]Ester M,Kriegel H P,Sander J,et al.A Density-based Algorithm for Discovering Clusters in Large Spatial Databases with Noise[C]//Proceedings of 1996 Inter-national Conference on Knowledge Discovering and Data Mining.New
York,USA:ACM Press,1996:226-231.
[5]Zhou Shuigeng,Zhou Aoying,Jin Wen,et al.FDBSCAN:A Fast DBSCAN Algorithm[J].Journal of Software,2000,11(6):735-744.
[6]Ma Yu,Gao Yuling,Song Shaoyun.The Algorithm of DBSCAN Based on Probability Distribution[C]//Pro-ceedings of the 5th International Symposium on IT in Medicine and Education.Xining,China:[s.n.],2014:2785-2792.
[7]Jahirabadkar S,Kulkarni P.Algorithm to Determine ε-distance Parameter in Density Based Clustering[J].Expert Systems with Applications,2014,41(6):2939-2946.
[8]Xiong Zhongyang,Chen Ruotian,Zhang Yufang,et al.Multi-density DBSCAN Algorithm Based on Density Levels Partitioning[J].Journal of Information and Computational Science,2012,9(10):2739-2749.
[9]Ankerst M,Breuning M,Kriegel H.OPTICS:Ordering Points to Identify the Clustering Structure[C]//Proceedings of ACM SIGMOD International Conference on Management of Data.New York,USA:ACM Press,1999:49-60.
[10]陈燕俐,洪龙,金达文,等.一种简单有效的基于密度的聚类分析算法[J].南京邮电学院学报,2005,25(4):24-29.
[11]曾依灵,许洪波,白硕.改进的OPTICS算法及其在文本聚类中的应用[J].中文信息学报,2008,22(1):51-55,60.
[12]Qiu Baozhi,Li Xiao.Grid-based Clustering Algorithm Based on Intersecting Partition and Density Estima-tion[C]//Proceedings of PAKDD’07.Berlin,Germany:Springer,2007,21(5):368-377.
[13]黄国顺,文翰.基于边界域的条件信息熵和属性约简[J].计算机应用,2015,35(10):2771-2776.
[14]Kohansal A,Rezakhah S.Modified Entropy Estimators for Testing Normality[J].Journal of Statistical Com-putation and Simulation,2016,86(3):1-16.
[15]戴阳阳,李朝锋,徐华.初始点优化与参数自适应的密度空间聚类算法[J].计算机工程,2016,42(1):203-209.
[16]Ratul D,Chakraborty S.Convex-Hull & DBSCAN Cluster-ing to Predict Future Weather[C]//Proceedings of 2015 International Conference and Workshop on Computing and Communication.Washington D.C.,USA:IEEE Press,2015:1-8.
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