VietMedKG: Knowledge Graph and Benchmark for Traditional Vietnamese Medicine

Traditional Vietnamese Medicine (TVM) and Traditional Chinese Medicine (TCM) have shared significant similarities due to their geographical location, cultural exchanges, and hot and humid climatic conditions. However, unlike TCM, which has substantial works published to construct a knowledge graph, there is a notable absence of a comprehensive knowledge graph for TVM. This article presents the first endeavor to build a knowledge graph for TVM based on extensive existing resources from TCM. We name our knowledge graph as VietMedKG. We propose a translation and filtration process to adapt TCM knowledge graphs to TVM, identifying the overlapping and unique elements of TVM. In addition, the constructed knowledge graph is then exploited further for developing a curated benchmark for the knowledge graph-based question-answering problem with the potential to support doctors and patients in assisting doctors and patients in identifying various diseases. Our work will not only bridge the gap between TCM and TVM but also set the foundation for future research into TVM community. Our source code is publicly available at https://github.com/HySonLab/VietMedKG .

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Publication Details

Journal
ACM Transactions on Asian and Low-Resource Language Information Processing
Published
2025-06-16
DOI
https://doi.org/10.1145/3744740
Citations
1
Primary Topic
Traditional Chinese Medicine Studies
Type
article
Field-Weighted Citation Impact
2.38
Controls
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article

VietMedKG: Knowledge Graph and Benchmark for Traditional Vietnamese Medicine

Truong Son Hy, Tam Trinh, Anh Dao, Thi Hong Nhung Hy
1 citations
ACM Transactions on Asian and Low-Resource Language Information Processing
Traditional Chinese Medicine Studies
2.38
article

VietMedKG: Knowledge Graph and Benchmark for Traditional Vietnamese Medicine

Truong Son Hy, Tam Trinh, Anh Dao, Thi Hong Nhung Hy
article en
1 citations

Abstract

Traditional Vietnamese Medicine (TVM) and Traditional Chinese Medicine (TCM) have shared significant similarities due to their geographical location, cultural exchanges, and hot and humid climatic conditions. However, unlike TCM, which has substantial works published to construct a knowledge graph, there is a notable absence of a comprehensive knowledge graph for TVM. This article presents the first endeavor to build a knowledge graph for TVM based on extensive existing resources from TCM. We name our knowledge graph as VietMedKG. We propose a translation and filtration process to adapt TCM knowledge graphs to TVM, identifying the overlapping and unique elements of TVM. In addition, the constructed knowledge graph is then exploited further for developing a curated benchmark for the knowledge graph-based question-answering problem with the potential to support doctors and patients in assisting doctors and patients in identifying various diseases. Our work will not only bridge the gap between TCM and TVM but also set the foundation for future research into TVM community. Our source code is publicly available at https://github.com/HySonLab/VietMedKG .

ACM Transactions on Asian and Low-Resource Language Information ProcessingVol. 24(7)
Hanoi National University of Education (VN), National Economics University (VN), University of Alabama at Birmingham (US), Michigan State University (US)
Openalex Percentile: Top 12%
Traditional Chinese Medicine Studies
2.38
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