Titlebook: Big Data Analytics; Methods and Applicat Saumyadipta Pyne,B.L.S. Prakasa Rao,S.B. Rao Book 2016 Springer India 2016 Big Data.Computational

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An Efficient Partition-Repetition Approach in Clustering of Big Data,ial emphasis on the characteristic of big data in this context. We develop an adaptation of a standard method that is more suitable to big data clustering when the data cloud is relatively regular with respect to inherent features. We also discuss a novel method for some special types of data where

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Online Graph Partitioning with an Affine Message Combining Cost Function, developed in order to minimize communication of computing nodes, should be considered in designing new cost functions for graph partitioning. In this paper, we propose a new cost function for graph partitioning which considers message combining. In this new cost function, we consider communication

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Application-Level Benchmarking of Big Data Systems,esearch, there is a pressing need for benchmarks that can provide objective evaluations of alternative technologies and solution approaches to a given big data problem. This chapter gives an introduction to big data benchmarking and presents different proposals and standardization efforts.

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Managing Large-Scale Standardized Electronic Health Records,em for managing large-scale standardized records in terms of data volume, velocity, and variety. Every proposed modification to logical layer has its pros and cons. In this chapter, we will discuss various aspects of the solutions proposed for managing standardized EHRs, and the approaches to adopt