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• W2473814966 abstract "Recent research has identified spatial association rule (SAR) mining as a promising technique for geographic pattern mining and knowledge discovery. Nevertheless, important spatial components embedded in the studied phenomenon, in particular complex spatial functional relations such as neighborhood effects and spatial spillover effects have largely been neglected. This article unravels this specific problem to enhance the effective application of SAR mining practices in spatial data analytics. The main discussion focuses on the specification of complex spatial components by means of spatial dependence properties of the data and on how to integrate them in the process of SAR mining. A comprehensive framework dubbed SpatialARMED is proposed for the effective extraction of spatial patterns. The framework is then showcased through its application to crime analysis." @default.
• W2473814966 created "2016-07-22" @default.
• W2473814966 creator A5000206320 @default.
• W2473814966 creator A5018141373 @default.
• W2473814966 date "2016-02-06" @default.
• W2473814966 modified "2023-10-04" @default.
• W2473814966 title "The SpatialARMED Framework: Handling Complex Spatial Components in Spatial Association Rule Mining" @default.
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• W2473814966 doi "https://doi.org/10.1111/gean.12094" @default.
• W2473814966 hasPublicationYear "2016" @default.
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