Abstract
In this fast growing Big Data oriented business world, all most every company is trying to identify new ways to capture and utilize unlimited stream of unstructured heterogeneous data efficiently. In this process companies are finding that Graph based representation of data is more beneficial and comfortable for their analysis methodologies. Development of Graph based tools are helpful for studying, transforming, visualizing and analyzing Big Data in the form of vertices and edges. Graphs are extremely useful to visualize hidden relationships among unstructured complex data sets. The popularity of Graphs has shown a stable growth with the evolution of the internet and social networks. Even though Graphs offer a flexible data structure, handling of Large-scale Graphs is an interesting research problem. Graph analysis and visualization are in the spotlight because of its ability to adapt it for social networking analysis systems. Sales and marketing managers are making use of Analysis and Visualization of Social networking Graph based system to meet their business targets and sustain at top position in the market. Successful implementation of Graph analytics revolves around quite a lot of key considerations such as collect the data, clean it, build the Graph, compresses, filters, transform, visualize and Analyze it. This paper concentrates on creating, transforming, visualizing and analyzing Large-scale Graphs from sample data pertaining to product purchase from Amazon social networking website.
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Mithili Devi, N., Kasireddy, S.R. (2019). Graph Analysis and Visualization of Social Network Big Data. In: Social Network Forensics, Cyber Security, and Machine Learning. SpringerBriefs in Applied Sciences and Technology(). Springer, Singapore. https://doi.org/10.1007/978-981-13-1456-8_8
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DOI: https://doi.org/10.1007/978-981-13-1456-8_8
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