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dc.contributor.authorLaha, Arnab Kumar
dc.date.accessioned2019-05-25T03:38:35Z
dc.date.available2019-05-25T03:38:35Z
dc.date.issued2016
dc.identifier.citationLaha, A.K. (2016). Statistical challenges with big data in management science in S. Pyne, B.L.S. Prakasa Ra o, S.B. Rao (Eds.), Big Data Analytics - Methods and Applications, (pp . 41- 55). New Delhi : Springer. DOI: 10.1007/978-81-322-3628-3_3en_US
dc.identifier.urihttp://hdl.handle.net/11718/21941
dc.description.abstractThis book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big Data standards; bench-marking of systems; and others. In addition to different applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modelling of high-dimensional data are also covered. The varied collection of themes in this volume introduces the reader to the richness of the emerging field of Big Data Analytics.en_US
dc.publisherSpringeren_US
dc.subjectBig Dataen_US
dc.subjectmanagement and financeen_US
dc.subjectmedicine and healthcareen_US
dc.titleStatistical challenges with big data in management scienceen_US
dc.title.alternativeBig Data Analytics - Methods and Applicationsen_US
dc.typeBook chapteren_US


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