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Construction of domain knowledge graph of dementia care / 中华护理杂志
Chinese Journal of Nursing ; (12): 432-438, 2024.
Article in Zh | WPRIM | ID: wpr-1027865
Responsible library: WPRO
ABSTRACT
Objective To construct a domain knowledge graph of dementia care,so as to provide the foundation and guarantee for the next intelligent application based on the knowledge graph.Methods A top-down approach was adopted to construct a domain knowledge graph of dementia care.Firstly,the ontology concept is constructed from the top level,namely the schema layer of knowledge graph.Then,instances are filled,and knowledge extraction is carried out from the existing data sources,and the extracted entities and relationships are filled into the pattern layer ontology database to complete the data layer construction of the knowledge graph.Finally,the"entity relationship entity"triplet data was input into the Neo4j graph database for storage.Results In this study,the personalized care plan set of 1 012 dementia cases was used as the corpus to construct a domain knowledge graph of dementia care.The knowledge graph takes people with dementia as the core,and unfolds,one by one,around basic characteristics,care problems,and care plans in a standardized"entity-relationship-entity"triplet format,forming a large knowledge network,which contains a total of 1 522 specific dementia care knowledge entities and 8 kinds of inter-entity relationships.Conclusion The domain knowledge graph of dementia care constructed in this study clearly and intuitively shows the global pedigree and logical path of knowledge,which provides an efficient and intelligent basic guarantee for the browsing,retrieval and application of dementia care knowledge,so as to realize personalized and intelligent management of people with dementia,break through the bottleneck of lack of professionals,improve the health outcomes of people with dementia,promote the implementation of inclusive pension services,and promote healthy aging.
Key words
Full text: 1 Database: WPRIM Language: Zh Journal: Chinese Journal of Nursing Year: 2024 Document type: Article
Full text: 1 Database: WPRIM Language: Zh Journal: Chinese Journal of Nursing Year: 2024 Document type: Article