Collect and Connect Data Leaves to Feature Concepts: Interactive Graph Generation Toward Well-being
This work addresses the challenge of data use and reuse for well-being applications, but it appears incremental as it builds on existing concepts of feature concepts and data leaves.
The paper tackles the problem of fostering creative thoughts for well-being by developing a semi-automatic method to generate graphs that connect data leaves (summaries of event flows) to feature concepts, rather than relying on fully automated generative AI.
Feature concepts and data leaves have been invented using datasets to foster creative thoughts for creating well-being in daily life. The idea, simply put, is to attach selected and collected data leaves that are summaries of event flows to be discovered from corresponding datasets, on the target feature concept representing the well-being aimed. A graph of existing or expected datasets to be attached to a feature concept is generated semi-automatically. Rather than sheer automated generative AI, our work addresses the process of generative artificial and natural intelligence to create the basis for data use and reuse.