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dc.contributor.authorBurguillo, Juan Carlos
dc.contributor.authorZúñiga Cañón, Claudia Liliana
dc.date.accessioned2020-03-06T21:40:58Z
dc.date.available2020-03-06T21:40:58Z
dc.date.issued2014-11-12
dc.identifier.issn03029743
dc.identifier.urihttps://repository.usc.edu.co/handle/20.500.12421/2898
dc.identifier.urihttps://doi.org/10.1007/978-3-319-12027-0_56
dc.description.abstractOne 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.language.isoenes
dc.publisherSpringer Verlages
dc.subjectUrban computinges
dc.subjectData mininges
dc.subjectDecision treees
dc.subjectWekaes
dc.titleApplying Data Mining in Urban Environments Using the Roles Model Approaches
dc.typeArticlees


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