Angelov, Plamen and Sadeghi Tehran, Pouria (2015) A nested hierarchy of dynamically evolving clouds for big data structuring and searching. Procedia Computer Science, 53. pp. 1-8. ISSN 1877-0509
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Abstract
The need to analyse big data streams and prescribe actions pro-actively is pervasive in nearly every industry. As growth of unstructured data increases, using analytical systems to assimilate and interpret images and videos as well as interpret structured data is essential. In this paper, we proposed a novel approach to transform image dataset into higher-level constructs that can be analysed more computationally efficiently, reliably and extremely fast. The proposed approach provides a high visual quality result between the query image and data clouds with hierarchical dynamically nested evolving structure. The results illustrate that the introduced approach can be an effective yet computationally efficient way to analyse and manipulate storedimages which has become the centre of attention of many professional fields and institutional sectors over the last few years.