FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3206335923> ?p ?o ?g. }

• W3206335923 endingPage "4337" @default.
• W3206335923 startingPage "4321" @default.
• W3206335923 abstract "Since first outbreak of respiratory disease in China, the Coronavirus epidemic (COVID-19) spread on a large scale, causing huge losses to individuals, families, communities and society in the country. The conventional research on the transmission process is basically to study the law or trend of the transmission of infectious diseases from a macro perspective. For in-depth study of the critical data of the newly confirmed patients, one effective way to improve the social isolation measures requires the formation of an organized tracking knowledge system for the confirmed patients and the personnel who have been removed, and the deep data mining and application. Knowledge graph (KG) is one of the irreplaceable techniques to quickly gather patient contact information and outbreak event, which reflecting the relationship between knowledge evolution and structure of novel Coronavirus. Therefore, this paper proposes a method for the analysis of COVID-19 epidemic situation using knowledge graph combined with interactive visual analysis. Firstly, based on the key factors of novel Coronavirus disease, the entity model of the patient, the relationship type of the patient and the expression of knowledge modeling were proposed, and the knowledge graph of the action track of the COVID-19 patient was deeply explored and comparative summarized. Secondly, in the process of constructing knowledge graph, conditional random field (CRF) algorithm is used to extract entity and knowledge. Meanwhile, to better analyze the disease relationship between patients, the semantic relationship of knowledge graph was combined with the visualization of knowledge graph, and the semantic model was verified by deep learning calculation and node attribute similarity. To discover the community detection of patients in the patient knowledge graph, this paper uses PageRank combined with Label propagation algorithms to discover community propagation in the network. Finally, COVID-19 epidemic situation was analyzed from confirmed patient data and multi-view collaborative interactions, such as map distribution visualization, knowledge graph visualization, and track visualization. The results show that the construction of a knowledge graph of COVID-19 patient activity is feasible for the transmission process, analysis of key nodes and tracing of activity tracks." @default.
• W3206335923 created "2021-10-25" @default.
• W3206335923 creator A5065884243 @default.
• W3206335923 date "2021-10-01" @default.
• W3206335923 modified "2023-09-26" @default.
• W3206335923 title "Construct a Knowledge Graph for China Coronavirus (COVID-19) Patient Information Tracking" @default.
• W3206335923 cites W2038705219 @default.
• W3206335923 cites W2153349010 @default.
• W3206335923 cites W2251135946 @default.
• W3206335923 cites W2517194566 @default.
• W3206335923 cites W2549900009 @default.
• W3206335923 cites W2550759377 @default.
• W3206335923 cites W2554926856 @default.
• W3206335923 cites W2615453028 @default.
• W3206335923 cites W2790265691 @default.
• W3206335923 cites W2893775232 @default.
• W3206335923 cites W2911391424 @default.
• W3206335923 cites W2922528227 @default.
• W3206335923 cites W2939592887 @default.
• W3206335923 cites W2945314865 @default.
• W3206335923 cites W2945623882 @default.
• W3206335923 cites W2951274974 @default.
• W3206335923 cites W3002539152 @default.
• W3206335923 cites W3003668884 @default.
• W3206335923 cites W3085321109 @default.
• W3206335923 doi "https://doi.org/10.2147/rmhp.s309732" @default.
• W3206335923 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/8544565" @default.
• W3206335923 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34707418" @default.
• W3206335923 hasPublicationYear "2021" @default.
• W3206335923 type Work @default.
• W3206335923 sameAs 3206335923 @default.
• W3206335923 citedByCount "6" @default.
• W3206335923 countsByYear W32063359232012 @default.
• W3206335923 countsByYear W32063359232021 @default.
• W3206335923 countsByYear W32063359232022 @default.
• W3206335923 countsByYear W32063359232023 @default.
• W3206335923 crossrefType "journal-article" @default.
• W3206335923 hasAuthorship W3206335923A5065884243 @default.
• W3206335923 hasBestOaLocation W32063359231 @default.
• W3206335923 hasConcept C120567893 @default.
• W3206335923 hasConcept C124101348 @default.
• W3206335923 hasConcept C132525143 @default.
• W3206335923 hasConcept C154945302 @default.
• W3206335923 hasConcept C207685749 @default.
• W3206335923 hasConcept C2522767166 @default.
• W3206335923 hasConcept C2987255567 @default.
• W3206335923 hasConcept C41008148 @default.
• W3206335923 hasConcept C80444323 @default.
• W3206335923 hasConceptScore W3206335923C120567893 @default.
• W3206335923 hasConceptScore W3206335923C124101348 @default.
• W3206335923 hasConceptScore W3206335923C132525143 @default.
• W3206335923 hasConceptScore W3206335923C154945302 @default.
• W3206335923 hasConceptScore W3206335923C207685749 @default.
• W3206335923 hasConceptScore W3206335923C2522767166 @default.
• W3206335923 hasConceptScore W3206335923C2987255567 @default.
• W3206335923 hasConceptScore W3206335923C41008148 @default.
• W3206335923 hasConceptScore W3206335923C80444323 @default.
• W3206335923 hasLocation W32063359231 @default.
• W3206335923 hasLocation W32063359232 @default.
• W3206335923 hasLocation W32063359233 @default.
• W3206335923 hasLocation W32063359234 @default.
• W3206335923 hasLocation W32063359235 @default.
• W3206335923 hasOpenAccess W3206335923 @default.
• W3206335923 hasPrimaryLocation W32063359231 @default.
• W3206335923 hasRelatedWork W2916853871 @default.
• W3206335923 hasRelatedWork W2923818335 @default.
• W3206335923 hasRelatedWork W3016646566 @default.
• W3206335923 hasRelatedWork W3191833430 @default.
• W3206335923 hasRelatedWork W3193273225 @default.
• W3206335923 hasRelatedWork W4210315291 @default.
• W3206335923 hasRelatedWork W4292070284 @default.
• W3206335923 hasRelatedWork W4310444679 @default.
• W3206335923 hasRelatedWork W4385459432 @default.
• W3206335923 hasRelatedWork W68685461 @default.
• W3206335923 hasVolume "Volume 14" @default.
• W3206335923 isParatext "false" @default.
• W3206335923 isRetracted "false" @default.
• W3206335923 magId "3206335923" @default.
• W3206335923 workType "article" @default.