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Erschienen in:
2007 | OriginalPaper | Buchkapitel
Discovering Emerging Patterns in Spatial Databases: A Multi-relational Approach
verfasst von : Michelangelo Ceci, Annalisa Appice, Donato Malerba
Erschienen in: Knowledge Discovery in Databases: PKDD 2007
Verlag: Springer Berlin Heidelberg
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Spatial Data Mining (SDM) has great potential in supporting public policy and in underpinning society functioning. One task in SDM is the discovery of characterization and peculiarities of communities sharing socio-economic aspects in order to identify potentialities, needs and public intervention. Emerging patterns (EPs) are a special kind of pattern which contrast two classes. In this paper, we face the problem of extracting EPs from spatial data. At this aim, we resort to a multi-relational approach in order to deal with the degree of complexity of discovering EPs from spatial data (i.e., (i) the spatial dimension implicitly defines spatial properties and relations, (ii) spatial phenomena are affected by autocorrelation). Experiments on real datasets are described.