Geospatial clustering in data-rich environments: features and issues

Geospatial clustering must be designed in such a way that it takes into account the special features of geoinformation and the peculiar nature of geographical environments in order to successfully derive geospatially interesting global concentrations and localized excesses. This paper examines families of geospaital clustering recently proposed in the data mining community and identifies several features and issues especially important to geospatial clustering in data-rich environments.

Lecture Notes in Computer Science

9th International Knowledge-Based Intelligent Information and Engineering Systems Conference 2005

3684

1611-3349

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N/A

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