Usporedite metode

	Analiza usmjerenih grafova znanja	Usmjereno otkrivanje zajednica
Područje	Analiza mreža	Analiza mreža
Obitelj	Machine learning	Machine learning
Godina nastanka	2000s–2010s	2008
Tvorac	Hogan, A. et al. (formalized); roots in Berners-Lee, T. et al. (Semantic Web)	Leicht, E. A. & Newman, M. E. J.; Rosvall, M. & Bergstrom, C. T.
Vrsta	Graph-based knowledge representation and inference	Graph partitioning / modularity optimization
Temeljni izvor	Hogan, A., Blomqvist, E., Cochez, M., d'Amato, C., Melo, G. D., Gutierrez, C., ... & Polleres, A. (2021). Knowledge graphs. ACM Computing Surveys, 54(4), 1–37.	Leicht, E. A. & Newman, M. E. J. (2008). Community structure in directed networks. Physical Review Letters, 100(11), 118703.
Drugi nazivi	directed KG analysis, knowledge graph mining, directed semantic graph analysis, KG reasoning	directed graph clustering, community detection in digraphs, directed modularity optimization, directed network partitioning
Srodne	6	6
Sažetak	Directed Knowledge Graph Analysis represents factual knowledge as a directed labeled multigraph of entities (nodes) and typed relations (directed edges), enabling structured reasoning, inference, and discovery over large heterogeneous datasets. The direction of edges encodes asymmetric relationships such as 'authored-by', 'causes', or 'is-a', making the graph semantically richer than undirected alternatives.	Directed community detection identifies densely interconnected groups of nodes in a directed network, accounting for the asymmetry of edges (e.g., A follows B does not imply B follows A). Adapting modularity or flow-based criteria to directed graphs reveals clusters that undirected methods systematically miss, making it essential for citation networks, follower graphs, and biological regulatory pathways.