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

Yukio Ohsawa, Tomohide Maekawa, Hiroki Yamaguchi, Hiro Yoshida, Kaira Sekiguchi
{"title":"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","authors":"Yukio Ohsawa, Tomohide Maekawa, Hiroki Yamaguchi, Hiro Yoshida, Kaira Sekiguchi","doi":"10.1609/aaaiss.v3i1.31241","DOIUrl":null,"url":null,"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.","PeriodicalId":516827,"journal":{"name":"Proceedings of the AAAI Symposium Series","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Collect and Connect Data Leaves to Feature Concepts: Interactive Graph Generation Toward Wellbeing\",\"authors\":\"Yukio Ohsawa, Tomohide Maekawa, Hiroki Yamaguchi, Hiro Yoshida, Kaira Sekiguchi\",\"doi\":\"10.1609/aaaiss.v3i1.31241\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":516827,\"journal\":{\"name\":\"Proceedings of the AAAI Symposium Series\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the AAAI Symposium Series\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1609/aaaiss.v3i1.31241\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the AAAI Symposium Series","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1609/aaaiss.v3i1.31241","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

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。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Collect and Connect Data Leaves to Feature Concepts: Interactive Graph Generation Toward Wellbeing
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Modes of Tracking Mal-Info in Social Media with AI/ML Tools to Help Mitigate Harmful GenAI for Improved Societal Well Being Embodying Human-Like Modes of Balance Control Through Human-In-the-Loop Dyadic Learning Constructing Deep Concepts through Shallow Search Implications of Identity in AI: Creators, Creations, and Consequences ASMR: Aggregated Semantic Matching Retrieval Unleashing Commonsense Ability of LLM through Open-Ended Question Answering
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1