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

Abstract

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 fail of making enough use of advanced logic reasoning, advanced artificial intelligence techniques, special-purpose programming languages, modern probabilistic and statistic theories, et. 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.

Keywords: Knowledge Graph Network, KGN-Prolog, Clinical Application of KGN-Prolog, Programming with KGN-Prolog on Vector Spaces, KGN-Prolog's Fuzzy, Deep and Multi-Modal Enhancement, Consultation and Argumentation as KGN-Prolog Programs, Resolution with Partial Unification