Novel Design and Implementation of Graph Mining for Big Data Network Analysis
Journal Title: International Journal of engineering Research and Applications - Year 2017, Vol 7, Issue 7
Abstract
The Research entitled Application of Graph Theory to Big Networks for Big Data” is an innovative idea having novel design and exemplar implementations on various case studies. Graph Mining strategies can be applied for Big Data Networks Analysis as specified by Literature survey. Big Data concern large-volume, complex, growing data sets with multiple, autonomous sources. With the fast development of networking, data storage, and the data collection capacity, Big Data are now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences. This paper presents a HACE theorem that characterizes the features of the Big Data revolution, and proposes a Big Data processing model, from the data mining perspective. This data-driven model involves demand-driven aggregation of information sources, mining and analysis, user interest modeling, and security and privacy considerations. We analyze the challenging issues in the data-driven model and also in the Big Data revolution. Index Terms: Graph Theory, Graph Mining, Big Data, Big Networks, Network Analysis Corresponding author: Sakshi Semwal
Authors and Affiliations
Dr. D. Shravani
Keywords
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- EP ID EP391860
- DOI 10.9790/9622-0707071625.
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