Logic Programming on Knowledge Graph Networks And its Application in Medical Domain

Fuente: arXiv
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Hauptverfasser: Wang, Chuanqing, Zhao, Zhenmin, Du, Shanshan, Fei, Chaoqun, Zhang, Songmao, Lu, Ruqian
Format: Preprint
Veröffentlicht: 2026
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author Wang, Chuanqing
Zhao, Zhenmin
Du, Shanshan
Fei, Chaoqun
Zhang, Songmao
Lu, Ruqian
author_facet Wang, Chuanqing
Zhao, Zhenmin
Du, Shanshan
Fei, Chaoqun
Zhang, Songmao
Lu, Ruqian
contents The rash development of knowledge graph research has brought big driving force to its application in many areas, including the medicine and healthcare domain. However, we have found that the application of some major information processing techniques on knowledge graph still lags behind. This defect includes the failure to make sufficient use of advanced logic reasoning, advanced artificial intelligence techniques, special-purpose programming languages, modern probabilistic and statistic theories et al. on knowledge graphs development and application. In particular, the multiple knowledge graphs cooperation and competition techniques have not got enough attention from researchers. This paper develops a systematic theory, technique and application of the concept 'knowledge graph network' and its application in medical and healthcare domain. Our research covers its definition, development, reasoning, computing and application under different conditions such as unsharp, uncertain, multi-modal, vectorized, distributed, federated. Almost in each case we provide (real data) examples and experiment results. Finally, a conclusion of innovation is provided.
format Preprint
id arxiv_https___arxiv_org_abs_2601_15347
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Logic Programming on Knowledge Graph Networks And its Application in Medical Domain
Wang, Chuanqing
Zhao, Zhenmin
Du, Shanshan
Fei, Chaoqun
Zhang, Songmao
Lu, Ruqian
Artificial Intelligence
Computation and Language
Machine Learning
The rash development of knowledge graph research has brought big driving force to its application in many areas, including the medicine and healthcare domain. However, we have found that the application of some major information processing techniques on knowledge graph still lags behind. This defect includes the failure to make sufficient use of advanced logic reasoning, advanced artificial intelligence techniques, special-purpose programming languages, modern probabilistic and statistic theories et al. on knowledge graphs development and application. In particular, the multiple knowledge graphs cooperation and competition techniques have not got enough attention from researchers. This paper develops a systematic theory, technique and application of the concept 'knowledge graph network' and its application in medical and healthcare domain. Our research covers its definition, development, reasoning, computing and application under different conditions such as unsharp, uncertain, multi-modal, vectorized, distributed, federated. Almost in each case we provide (real data) examples and experiment results. Finally, a conclusion of innovation is provided.
title Logic Programming on Knowledge Graph Networks And its Application in Medical Domain
topic Artificial Intelligence
Computation and Language
Machine Learning
url https://arxiv.org/abs/2601.15347