焦利民, 洪晓峰, 刘耀林. 空间和属性双重约束下的自组织空间聚类研究[J]. 武汉大学学报 ( 信息科学版), 2011, 36(7): 862-866.
引用本文: 焦利民, 洪晓峰, 刘耀林. 空间和属性双重约束下的自组织空间聚类研究[J]. 武汉大学学报 ( 信息科学版), 2011, 36(7): 862-866.
JIAO Limin, HONG Xiaofeng, LIU Yaolin. Self-organizing Spatial Clustering Under Spatial and Attribute Constraints[J]. Geomatics and Information Science of Wuhan University, 2011, 36(7): 862-866.
Citation: JIAO Limin, HONG Xiaofeng, LIU Yaolin. Self-organizing Spatial Clustering Under Spatial and Attribute Constraints[J]. Geomatics and Information Science of Wuhan University, 2011, 36(7): 862-866.

空间和属性双重约束下的自组织空间聚类研究

Self-organizing Spatial Clustering Under Spatial and Attribute Constraints

  • 摘要: 形式化定义了双重聚类的聚类准则及其判定方法,提出了双重聚类的两步法求解思路和自组织双重聚类算法。通过实例验证了该算法的可行性,自组织双重聚类可以发现非空间属性的聚集、延伸等空间分布特征,可以发现任意复杂形状的聚类,并降低了人为影响。

     

    Abstract: Spatial clustering under spatial and attribute constraints is the clustering analysis on the spatial dataset with non-spatial attributes,which is named dual clustering.The result of dual clustering should be spatially continuous and attributively aggregative.The essence of dual clustering is to find out the clustering and distribution rules of non-spatial attributes.This paper presents the formalized definition of dual clustering,proposes the two-step strategy and self-organizing dual clustering algorithm.Case study verifies the algorithm and shows that the self-organizing dual spatial clustering can find the spatial distribution rules of non-spatial attributes,such as clustering and stretching.Self-organizing dual clustering can detect clusters with complicated shape and reduces the artificial influence.

     

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