Improve performance of Interactive Visualization for Large Scale Big Data Networks


Authors : Neelam Matva,Manish Suroliya.

Volume/Issue : Volume 1 - 2016, Issue 6 - September

Google Scholar : https://goo.gl/QE0bVN

Scribd : https://goo.gl/HJF1cC

In this particular thesis, we are providing statistical modelling of a big data network. We are exploring the properties of the network like node degree distribution and coefficient of cluster for the purpose of analyzing various network, such as Directed Weighted, Directed Underweight, Undirected Weighted as well as Undirected Unweighted. There are thousands of different data points, which are normally statistical graphics which can come together to provide a cluttered view. If we consider this need to better the interactive visualization for a much bigger database then we may be developing a Pixel Based Overlay Network algorithm inside the MATLAB for the purpose of statistical modelling and visualization of the big picture data network. We are also testing the Pixel Based Overlay Network for the purpose of real world and big scale networks.

Keywords : Statistical modeling, Large Scale Network, Big Data,Degree Distribution, Cluster Coefficient.

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Paper Submission Last Date
31 - July - 2020

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