Knowledge Discovery and Data Visualization: Theories and Perspectives

Knowledge Discovery and Data Visualization: Theories and Perspectives

Kijpokin Kasemsap (Suan Sunandha Rajabhat University, Bangkok, Thailand)
DOI: 10.4018/IJOCI.2017070105
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Abstract

This article reviews the literature in the search for the theories and perspectives of knowledge discovery and data visualization. The literature review highlights the overview of knowledge discovery; Knowledge Discovery in Databases (KDD); Knowledge Discovery in Textual Databases (KDT); the overview of data visualization; the significant perspectives on data visualization; data visualization and big data; and data visualization and statistical literacy. Knowledge discovery is the process of searching for hidden knowledge in the massive amounts of data that individuals are technically capable of generating and storing. Data visualization is an easy way to convey concepts in a universal manner. Organizations, that utilize knowledge discovery and data visualization, are more likely to find both knowledge and information they need when they need them. The findings present valuable insights and further understanding of the way in which knowledge discovery and data visualization efforts should be focused.
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Theoretical And Practical Review Of The Literature

The literature review indicates the overview of knowledge discovery; Knowledge Discovery in Databases (KDD); Knowledge Discovery in Textual Databases (KDT); the overview of data visualization; the significant perspectives on data visualization; data visualization and big data; and data visualization and statistical literacy.

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