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Analiza grafova znanja×Analiza difuzije na mreži×
OblastAnaliza mrežaAnaliza mreža
PorodicaMachine learningMachine learning
Godina nastanka2012–20161927 (epidemic roots); network formalization 1990s–2000s
TvoracEhrlinger, L. & Wöß, W.; Google (popularized)Kermack, W. O. & McKendrick, A. G.
TipGraph-based knowledge representation and analysisSimulation / analytical model
Temeljni izvorEhrlinger, L. & Wöß, W. (2016). Towards a Definition of Knowledge Graphs. In Proceedings of the SEMANTICS Posters and Demos Track (SEMANTiCS 2016). CEUR Workshop Proceedings, vol. 1695. link ↗Kermack, W. O. & McKendrick, A. G. (1927). A contribution to the mathematical theory of epidemics. Proceedings of the Royal Society of London A, 115(772), 700–721. DOI ↗
Drugi naziviKG analysis, semantic graph analysis, knowledge base graph analysis, entity-relation graph analysisdiffusion on networks, information diffusion, contagion spreading model, network propagation model
Srodne55
SažetakKnowledge Graph Analysis is a framework for representing, storing, and reasoning over structured factual knowledge as a directed graph of entities and typed relations. Entities (nodes) and relationships (edges) are expressed as subject–predicate–object triples, enabling rich querying, inference, and integration of heterogeneous data sources across domains such as biomedical research, e-commerce, and scientific literature.Network diffusion analysis models how information, diseases, behaviors, or innovations spread across a graph of nodes and edges. Drawing on classical epidemic theory (SI, SIR, SIS) and modern network science, it tracks which nodes become infected, how quickly, and whether the spread reaches a global cascade or dies out locally.
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ScholarGateUporedite metode: Knowledge Graph Analysis · Network Diffusion Analysis. Preuzeto 2026-06-15 sa https://scholargate.app/sr/compare