Multimodal reasoning for nutrition and human health via knowledge graph embedding

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成果类型：

会议论文

作者：

Chengcheng Fu;Yanan Yao;Jieyu Wu;Weizhong Zhao;Tingting He;...

作者机构：

School of Computer, Central China Normal University, WuHan, PR China

Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University, WuHan, PR China

National Language Resources Monitor Research Center for Network Media, Central China Normal University, WuHan, PR China

National Engineering Research Center for E-Learning, Central China Normal University, WuHan, PR China

[Chengcheng Fu; Tingting He] School of Computer, Central China Normal University, WuHan, PR China<&wdkj&>National Engineering Research Center for E-Learning, Central China Normal University, WuHan, PR China<&wdkj&>Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University, WuHan, PR China<&wdkj&>National Language Resources Monitor Research Center for Network Media, Central China Normal University, WuHan, PR China

语种：

英文

关键词：

Knowledge graph;Multimodal embedding;Knowledge reasoning;Nutrition;Human health

年：

2023

页码：

1901-1904

会议名称：

2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

会议论文集名称：

2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

会议时间：

05 December 2023

会议地点：

Istanbul, Turkiye

出版者：

IEEE

ISBN：

979-8-3503-3749-5

DOI：

10.1109/BIBM58861.2023.10385745

基金类别：

10.13039/501100001809-National Natural Science Foundation of China 10.13039/501100003819-Natural Science Foundation of Hubei Province

机构署名：

本校为第一机构

院系归属：

计算机学院

国家数字化学习工程技术研究中心

摘要：

The established links between nutrition and human health are widely acknowledged. Dietary nutrients play a crucial role in regulating gut microbial communities, influencing various human diseases. With a growing number of related studies, there’s a need to systematically organize these associations for coherent knowledge reasoning. However, due to the diverse and extensive nature of the knowledge landscape, significant challenges persist. To address this, we propose an approach using multimodal data and knowledge embeddings for effective knowl...

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Multimodal reasoning for nutrition and human health via knowledge graph embedding

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