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A Nested Hierarchy of Dynamically Evolving Clouds for Big Data Structuring and Searching

机译:动态演化云的嵌套层次结构,用于大数据结构和搜索

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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 stored-images which has become the centre of attention of many professional fields and institutional sectors over the last few years.
机译:几乎每个行业都普遍需要分析大数据流并主动制定措施。随着非结构化数据的增长,使用分析系统来同化和解释图像和视频以及解释结构化数据至关重要。在本文中,我们提出了一种将图像数据集转换为高级结构的新颖方法,该方法可以更高效,可靠和快速地进行分析。所提出的方法通过分层动态嵌套的演化结构,在查询图像和数据云之间提供了高质量的视觉效果。结果表明,引入的方法可以是一种有效且计算效率高的分析和处理存储图像的方法,在过去的几年中,该方法已成为许多专业领域和机构领域关注的焦点。

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