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dc.contributor.authorBibri, Simon Elias
dc.contributor.authorKrogstie, John
dc.date.accessioned2019-03-04T12:41:07Z
dc.date.available2019-03-04T12:41:07Z
dc.date.created2019-01-13T18:37:17Z
dc.date.issued2018
dc.identifier.isbn978-1-4503-6562-8
dc.identifier.urihttp://hdl.handle.net/11250/2588493
dc.description.abstractThere has recently been much enthusiasm about the possibilities created by the big data deluge to better understand, monitor, analyze, and plan modern cities to improve their contribution to the goals of sustainable development. Indeed, much of our knowledge of urban sustainability has been gleaned from studies that are characterized by data scarcity. Therefore, this paper endeavors to develop a systematic framework for urban sustainability analytics based on a cross-industry standard process for data mining. The intention is to enable well-informed decision-making and enhanced insights in relation to diverse urban domains. We argue that there is tremendous potential to transform and advance the knowledge of smart sustainable cities through the creation of a big data deluge that seeks to provide much more sophisticated, wider-scale, finer-grained, real-time understanding, and control of various aspects of urbanity in the undoubtedly upcoming Exabyte Age.nb_NO
dc.language.isoengnb_NO
dc.publisherAssociation for Computing Machinery (ACM)nb_NO
dc.relation.ispartofSCA '18: Proceedings of the 3rd International Conference on Smart City Applications
dc.titleThe Big Data Deluge for Transforming the Knowledge of Smart Sustainable Cities: A Data Mining Framework for Urban Analyticsnb_NO
dc.typeChapternb_NO
dc.description.versionacceptedVersionnb_NO
dc.identifier.doi10.1145/3286606.3286788
dc.identifier.cristin1655691
dc.description.localcode© ACM, 2018. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Transactions of Computing Education, https://doi.org/10.1145/3286606.3286788nb_NO
cristin.unitcode194,63,10,0
cristin.unitnameInstitutt for datateknologi og informatikk
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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