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Development of a Method for Analyzing and Visualizing Concept Hierarchies based on Relational Attributes and its Application on Public Open Datasets

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2021, 26(9), pp.13-25
  • DOI : 10.9708/jksci.2021.26.09.013
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : May 27, 2021
  • Accepted : September 15, 2021
  • Published : September 30, 2021

Suk-Hyung Hwang 1

1선문대학교

Accredited

ABSTRACT

In the age of digital innovation based on the Internet, Information and Communication and Artificial Intelligence technologies, huge amounts of datasets are being generated, collected, accumulated, and opened on the web by various public institutions providing useful and public information. In order to analyse, gain useful insights and information from data, Formal Concept Analysis(FCA) has been successfully used for analyzing, classifying, clustering and visualizing data based on the binary relation between objects and attributes in the dataset. In this paper, we present an approach for enhancing the analysis of relational attributes of data within the extended framework of FCA, which is designed to classify, conceptualize and visualize sets of objects described not only by attributes but also by relations between these objects. By using the proposed tool, RCA wizard, several experiments carried out on some public open datasets demonstrate the validity and usability of our approach on generating and visualizing conceptual hierarchies for extracting more useful knowledge from datasets. The proposed approach can be used as an useful tool for effective data analysis, classifying, clustering, visualization and exploration.

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This paper was written with support from the National Research Foundation of Korea.
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