Automatic classification of location contexts with decision trees

• Autor(es): Santos, Maribel Yasmina ; Moreira, Adriano
• Data: 2006
• Identificador Persistente: http://hdl.handle.net/1822/5582
• Origem: RepositóriUM - Universidade do Minho
• Assunto(s): Location contexts; Space models; Data mining; Decision trees; Clustering
• Tipo de Documento: Documento de conferência
• Idioma: Inglês

Descrição

Location contexts are geographic regions, with well defined boundaries, that can be used to characterize the context of the persons lying inside them. In this paper we describe a process that exploits the increasing availability of geographic data to automatically create and classify location contexts. The pro-posed process generates new geographic regions from a database of Points Of Interest through the use of spatial clustering techniques, and classifies them automatically using a decision tree based method. Some preliminary results demonstrate the validity of this approach, while suggesting that a richer geographic database could produce location contexts of higher quality.