MOSES: combining automated ontology construction with a multi-agent system for explainable chemical knowledge reasoning

MOSES: combining automated ontology construction with a multi-agent system for explainable chemical knowledge reasoning, Sun, Yingkai, Xu, Feiyang, Liang, Huadong, Fan, Xianghui, Wan, Guozhu, Zhong, Wenwan, Jiang, Jun, Li, Xin, Chen, Linjiang

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Publication Details

Journal
AI for Science
Published
2025-12-25
DOI
https://doi.org/10.1088/3050-287x/ae3127
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
0.00

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article

MOSES: combining automated ontology construction with a multi-agent system for explainable chemical knowledge reasoning

Huadong Liang, Yingkai Sun, Guozhu Wan, Linjiang Chen et al.
AI for Science
Machine Learning in Materials Science
article

MOSES: combining automated ontology construction with a multi-agent system for explainable chemical knowledge reasoning

Huadong Liang, Yingkai Sun, Guozhu Wan, Linjiang Chen, Xin Li, Jun Jiang, Wenwan Zhong, Feiyang Xu, Xianghui Fan
article en

Abstract

MOSES: combining automated ontology construction with a multi-agent system for explainable chemical knowledge reasoning, Sun, Yingkai, Xu, Feiyang, Liang, Huadong, Fan, Xianghui, Wan, Guozhu, Zhong, Wenwan, Jiang, Jun, Li, Xin, Chen, Linjiang

AI for ScienceVol. 2(1)
University of Science and Technology of China (CN), Anhui University (CN), Hefei University of Technology (CN), University College Birmingham (GB), Hefei National Center for Physical Sciences at Nanoscale (CN), Artificial Intelligence Research Institute (ES), University of Birmingham (GB)
National Natural Science Foundation of China, Chinese Academy of Sciences, University of Science and Technology of China
Openalex Percentile: Top 48%
Machine Learning in Materials Science
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MOSES: combining automated ontology construction with a multi-agent system for explainable chemical knowledge reasoning — Huadong Liang, Yingkai Sun, et al. · AI for Science (2025) | TGRS Research Map | TGRS