Σύγκριση μεθόδων

	Ανάλυση Πολυεπίπεδων Γράφων Γνώσης	Ανάλυση Κοινωνικών Δικτύων
Πεδίο	Ανάλυση Δικτύων	Ανάλυση Δικτύων
Οικογένεια	Machine learning	Machine learning
Έτος προέλευσης	2014–2016	1934 (sociometry); 1994 (modern formalization)
Δημιουργός	Kivela, M. et al.; Nickel, M. et al.	Moreno, J.L.; formalized by Wasserman & Faust
Τύπος	Graph-based analytical framework	Structural/relational analysis framework
Θεμελιώδης πηγή	Kivela, M., Arenas, A., Barthelemy, M., Gleeson, J. P., Moreno, Y., & Porter, M. A. (2014). Multilayer networks. Journal of Complex Networks, 2(3), 203–271.	Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1
Εναλλακτικές ονομασίες	multi-relational knowledge graph analysis, multilayer KG analysis, multi-relational graph analysis, multiplex knowledge graph analysis	SNA, network analysis, sociometric analysis, relational analysis
Συναφείς	5	5
Σύνοψη	Multilayer knowledge graph analysis treats a knowledge base as a stack of relation-specific network layers sharing the same entity set, enabling simultaneous reasoning across relation types. Unlike a flat single-layer graph, it preserves the semantic distinctions between relation types and supports cross-layer link prediction, entity alignment, and community detection grounded in multilayer network theory.	Social Network Analysis (SNA) is a structural method that maps and measures relationships and flows between people, groups, organizations, or other entities modeled as nodes connected by ties (edges). Rather than focusing on individual attributes, SNA reveals how the pattern of connections shapes behavior, influence, information flow, and outcomes within a system.