A Socratic RAG Approach to Connect Natural Language Queries on Research Topics with Knowledge Organization Systems
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arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866929723703033856 |
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| author | Lefton, Lew Rong, Kexin Dankhara, Chinar Ghemri, Lila Kausar, Firdous Hamdallahi, A. Hannibal |
| author_facet | Lefton, Lew Rong, Kexin Dankhara, Chinar Ghemri, Lila Kausar, Firdous Hamdallahi, A. Hannibal |
| contents | In this paper, we propose a Retrieval Augmented Generation (RAG) agent that maps natural language queries about research topics to precise, machine-interpretable semantic entities. Our approach combines RAG with Socratic dialogue to align a user's intuitive understanding of research topics with established Knowledge Organization Systems (KOSs). The proposed approach will effectively bridge "little semantics" (domain-specific KOS structures) with "big semantics" (broad bibliometric repositories), making complex academic taxonomies more accessible. Such agents have the potential for broad use. We illustrate with a sample application called CollabNext, which is a person-centric knowledge graph connecting people, organizations, and research topics. We further describe how the application design has an intentional focus on HBCUs and emerging researchers to raise visibility of people historically rendered invisible in the current science system. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_15005 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Socratic RAG Approach to Connect Natural Language Queries on Research Topics with Knowledge Organization Systems Lefton, Lew Rong, Kexin Dankhara, Chinar Ghemri, Lila Kausar, Firdous Hamdallahi, A. Hannibal Computation and Language Artificial Intelligence Human-Computer Interaction I.2.7; F.4.1 In this paper, we propose a Retrieval Augmented Generation (RAG) agent that maps natural language queries about research topics to precise, machine-interpretable semantic entities. Our approach combines RAG with Socratic dialogue to align a user's intuitive understanding of research topics with established Knowledge Organization Systems (KOSs). The proposed approach will effectively bridge "little semantics" (domain-specific KOS structures) with "big semantics" (broad bibliometric repositories), making complex academic taxonomies more accessible. Such agents have the potential for broad use. We illustrate with a sample application called CollabNext, which is a person-centric knowledge graph connecting people, organizations, and research topics. We further describe how the application design has an intentional focus on HBCUs and emerging researchers to raise visibility of people historically rendered invisible in the current science system. |
| title | A Socratic RAG Approach to Connect Natural Language Queries on Research Topics with Knowledge Organization Systems |
| topic | Computation and Language Artificial Intelligence Human-Computer Interaction I.2.7; F.4.1 |
| url | https://arxiv.org/abs/2502.15005 |