Journal of information and communication convergence engineering

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Optimization for Large-Scale n-ary Family Tree Visualization

  • Kyoungju, Min (Department of Sino-Korean Literature, Chungnam National University) ;
  • Jeongyun, Cho (Department of Sino-Korean Literature, Chungnam National University) ;
  • Manho, Jung (Department of Sino-Korean Literature, Chungnam National University) ;
  • Hyangbae, Lee (Department of Sino-Korean Literature, Chungnam National University)
  • Received : 2022.08.13
  • Accepted : 2022.10.18
  • Published : 2023.03.31
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Abstract

The family tree is one of the key elements of humanities classics research and is very important for accurately understanding people or families. In this paper, we introduce a method for automatically generating a family tree using information on interpersonal relationships (IIPR) from the Korean Classics Database (KCDB) and visualize interpersonal searches within a family tree using data-driven document JavaScript (d3.js). To date, researchers of humanities classics have wasted considerable time manually drawing family trees to understand people's influence relationships. An automatic family tree builder analyzes a database that visually expresses the desired family tree. Because a family tree contains a large amount of data, we analyze the performance and bottlenecks according to the amount of data for visualization and propose an optimal way to construct a family tree. To this end, we create an n-ary tree with fake data, visualize it, and analyze its performance using simulation results.

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References

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