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

Yukio Ohsawa, Tomohide Maekawa, Hiroki Yamaguchi, Hiro Yoshida, Kaira Sekiguchi
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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.
收集数据并将其与特征概念联系起来:生成交互式图表,实现幸福生活
特征概念和数据叶的发明是为了促进通过使用数据集来创造社会和物质福祉的想法。简单地说,这个想法是将选定和收集的数据叶(即从相应数据集中发现的事件流摘要)与代表福祉个人和福祉社会预期情景的目标特征概念相联系。以数据叶形式附加在特征概念上的现有或预期数据集图是半自动生成的。我们的工作不是纯粹的自动匹配生成式人工智能,而是通过人工智能和自然智能的生成过程,为收集和连接有用数据奠定基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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