Spectral Clustering of Attributed Multi-relational Graphs
Ylli Sadikaj, Yllka Velaj, Sahar Behzadi, Claudia Plant
Abstract
Graph clustering aims at discovering a natural grouping of the nodes such that similar nodes are assigned to a common cluster. Many different algorithms have been proposed in the literature: for simple graphs, for graphs with attributes associated to nodes, and for graphs where edges represent different types of relations among nodes. However, complex data in many domains can be represented as both attributed and multi-relational networks.
Topics & Concepts
Categorical variableCluster analysisComputer scienceTheoretical computer scienceEmbeddingData miningRelational databaseTopological graph theoryGraphArtificial intelligenceMachine learningLine graphPathwidthComplex Network Analysis TechniquesAdvanced Clustering Algorithms ResearchAdvanced Graph Neural Networks