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Inconsistencies in big data

机译:大数据不一致

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摘要

We are faced with a torrent of data generated and captured in digital form as a result of the advancement of sciences, engineering and technologies, and various social, economical and human activities. This big data phenomenon ushers in a new era where human endeavors and scientific pursuits will be aided by not only human capital, and physical and financial assets, but also data assets. Research issues in big data and big data analysis are embedded in multi-dimensional scientific and technological spaces. In this paper, we first take a close look at the dimensions in big data and big data analysis, and then focus our attention on the issue of inconsistencies in big data and the impact of inconsistencies in big data analysis. We offer classifications of four types of inconsistencies in big data and point out the utility of inconsistency-induced learning as a tool for big data analysis.
机译:随着科学,工程和技术的发展以及各种社会,经济和人类活动的发展,我们面临着大量以数字形式生成和捕获的数据。这种大数据现象进入了一个新时代,在这个新时代中,不仅人力资本,实物和金融资产,而且数据资产也将为人类的努力和科学追求提供帮助。大数据和大数据分析的研究问题被嵌入到多维科学技术空间中。在本文中,我们首先仔细研究大数据和大数据分析的维度,然后将注意力集中在大数据不一致的问题以及不一致对大数据分析的影响上。我们提供了大数据中四种不一致类型的分类,并指出了不一致引发的学习作为大数据分析工具的效用。

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