Applying Data Mining in Urban Environments Using the Roles Model Approach

dc.contributor.author	Burguillo, Juan Carlos
dc.contributor.author	Zúñiga Cañón, Claudia Liliana
dc.date.accessioned	2020-03-06T21:40:58Z
dc.date.available	2020-03-06T21:40:58Z
dc.date.issued	2014-11-12
dc.description.abstract	One of the main challenges in urban computing is to interpret the behaviors of the individuals, and so to provide services for suppling their needs. Data mining offers very powerful tools that can be used to analyze data in urban environments. Our research uses the UrbanContext roles model to identify the states of the individuals within urban environments. Then, it applies supervised classification data mining techniques to the results obtained, and uses decision trees in order to facilitate the analysis of the individuals’ behavior. Finally, we present the prediction results obtained from a study made about the roles that individuals adopt depending on their context. From these data we successfully predict the different types of services we can offer in an urban environment.	es
dc.identifier.issn	03029743
dc.identifier.uri	https://repositorio.usc.edu.co/handle/20.500.12421/2898
dc.identifier.uri	https://doi.org/10.1007/978-3-319-12027-0_56
dc.language.iso	en	es
dc.publisher	Springer Verlag	es
dc.subject	Urban computing	es
dc.subject	Data mining	es
dc.subject	Decision tree	es
dc.subject	Weka	es
dc.title	Applying Data Mining in Urban Environments Using the Roles Model Approach	es
dc.type	Article	es

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