| Project/Area Number |
19K12132
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 61030:Intelligent informatics-related
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| Research Institution | 大学共同利用機関法人情報・システム研究機構(機構本部施設等) |
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Principal Investigator |
Kim Jin-Dong 大学共同利用機関法人情報・システム研究機構(機構本部施設等), データサイエンス共同利用基盤施設, 特任准教授 (40536893)
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| Project Period (FY) |
2019-04-01 – 2024-03-31
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| Project Status |
Completed (Fiscal Year 2023)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2021: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2020: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2019: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Keywords | Natural Language / Dialog Interface / User Interface / Database / Data Science / Large Language Models / Customized GPT / Large Language Model / ChatGPT / dialog / intelligent agent / natural language query / database search / task-oriented dialog / intent detection / dialog agent / intelligent interface / agent / search / question answering / data science |
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| Outline of Research at the Start |
Data science is becoming a new paradigm of science, and a lot of investment has been made to develop science data. However, scientists are often unaware of how to access science data. Meanwhile, there has been increasing interest in the technology of conversational agent (CA), which can talk with users in human language, helping them accomplish certain tasks.
The research is to investigate the potential of CA technology for search-oriented dialogs to help scientists access science data. We expect it to contribute to advancing the CA technology, and improving the environment of data science.
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| Outline of Final Research Achievements |
The primary outputs of this research include Anatomy3DExplorer, a customized GPT developed for searching human anatomy 3D models (currently available on the GPT store), the dialog interface implemented in LODQA, and a web-based user interface for analyzing and annotating dialogs, integrated as a feature of TextAE. Currently, Anatomy3DExplorer is successfully being utilized by the developers of BodyParts3D, a database of anatomical 3D models. A paper detailing our findings has been submitted to the journal of Genomics & Informatics and is currently under review. Overall, we have demonstrated that search-oriented dialog systems can be effectively developed leveraging LLMs.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究成果は、LLMを活用することで自然言語ダイアログインターフェースを効果的に開発できることを示している。この成果は既に他のデータベース検索インターフェースの開発にも拡張されている。学術的には、LLMが人間の知能とデータに埋め込まれた知能を結びつける効果的なレイヤーを提供することを示している。社会的には、データベース検索スキルを持たないユーザーに対してデータベースにアクセスするための実用的な手段を提供できることを示している。これは、一般の人々が専門知識により容易にアクセスできるようになることを意味する。
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