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The data descriptions of the units are called "symbolic" when they are more complex than standard ones, due to the fact that they contain internal variations and are structured. Symbolic data arise from many sources, for instance when summarizing huge Relational Data Bases by their underlying...
Census data mining has great potential both in business development and in good public policy, but still must be solved in this field a number of research issues. In this paper, problems related to the geo-referenciation of census data are considered. In particular, the accommodation of the...
Politicians, planners and social scientists have an increasing need for tools clarifying the spatial distribution of relevant features. Special interest is in predicting changes in a what-if analysis: what would happen if we change some features in a specific way. To predict future developments...
The volume of data being produced for administrative purposes is increasing rapidly. Data must be analysed in order to extract useful information to support decision making. The demand for evidence-based information means that the analysis must be conducted according to the principles of...
The paper describes a system for spatial data mining illustrating its features by an application to spatial census data. Using census data for data mining includes specific challenges. Because of data privacy regulations, census data are generally available for analysis only in aggregated form....
In the competitive environments, in which all sorts of organisations move it is of utmost importance to have information about clients. Public databases offer information about households and families. However, the non-crossed and non-georeferenced format of these databases often makes it...
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