Collect and Connect Data Leaves to Feature Concepts: Interactive Graph Generation Toward Wellbeing

Authors

  • Yukio Ohsawa School of Engineering, The University of Tokyo, Tokyo 113-8656 Japan
  • Tomohide Maekawa Trust Architecture, Inc., Tokyo 107-0052 Japan
  • Hiroki Yamaguchi Trust Architecture, Inc., Tokyo 107-0052 Japan
  • Hiro Yoshida School of Engineering, The University of Tokyo, Tokyo 113-8656 Japan
  • Kaira Sekiguchi School of Engineering, The University of Tokyo, Tokyo 113-8656 Japan

DOI:

https://doi.org/10.1609/aaaiss.v3i1.31241

Keywords:

Impact of GenAI on Social and Individual Well-being

Abstract

Feature concepts and data leaves have been invented to foster thoughts for creating social and physical well-being through the use of datasets. The idea, simply put, is to at-tach selected and collected Data Leaves that are summaries of event flows to be discovered from corresponding datasets, on the target Feature Concept representing the expected scenarios of well-being individuals and well-being society. A graph of existing or expected datasets, attached in the form of Data Leaves on a Feature Concept, was generated semi-automatically. Rather than sheer auto-mated generative AI, our work addresses the process of generative artificial and natural intelligence to create the basis for collecting and connecting useful data.

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Published

2024-05-20

Issue

Section

Impact of GenAI on Social and Individual Well-being