Fengfeng He; Ling Zhang; Chong Teng; Dan Xie; Wei Qu

doi:https://doi.org/10.2991/jaims.d.200902.001

Authors

Fengfeng He School of Information Engineering, Hubei University of Chinese Medicine, Hubei, China https://orcid.org/0000-0002-3701-5009
Ling Zhang School of Public Health, Wuhan University of Science and Technology, Hubei, China https://orcid.org/0000-0002-5160-8900
Chong Teng School of Cyber Science and Engineering, Wuhan University, Hubei, China
Dan Xie School of Information Engineering, Hubei University of Chinese Medicine, Hubei, China https://orcid.org/0000-0001-8890-0529
Wei Qu School of Public Health, Wuhan University of Science and Technology, Hubei, China

DOI:

https://doi.org/10.2991/jaims.d.200902.001

Keywords:

Intestinal cells, Knowledge graph, Knowledge base, SPARQL query,

Abstract

Intestinal cells play a significant role in human physiological metabolism, immune protection, and development and control of nervous system diseases. With the flourishing development of artificial intelligence technology and arrival of intestinal cellular research enthusiasm, how to obtain knowledge of intestinal cells from a sea of medical literature and realize knowledge visualization has brought great challenges to medical researchers. At present, knowledge graph of intestinal cells has not been studied. In this paper, we present two processes to construct a knowledge graph of intestinal cells: conceptual layer design and instance layer construction. Conceptual layer design defines data model of knowledge graph. In the process of constructing instance layer, cells are regarded as basic conceptual unit to systematically sort out intestinal cell terminology, acquired data is pre-processed, and then mapped into knowledge graph to construct a knowledge base. We provide several SPARQL query cases, by which medical workers can efficiently obtain knowledge they require from the knowledge base, thereby better serving medical researches.

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Research on Construction of Knowledge Graph of Intestinal Cells

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