Relation Learning on Social Networks with Multi-Modal Graph Edge Variational Autoencoders
Carl Yang, Jieyu Zhang, Haonan Wang, Sha Li, Myungwan Kim, Matt Walker, Yiou Xiao, Jiawei Han
Abstract
While node semantics have been extensively explored in social networks, little research attention has been paid to pro le edge semantics, i.e., social relations. Ideal edge semantics should not only show that two users are connected, but also why they know each other and what they share in common. However, relations in social networks are often hard to pro le, due to noisy multi-modal signals and limited user-generated ground-truth labels.
Topics & Concepts
Semantics (computer science)ModalComputer scienceRelation (database)Theoretical computer scienceEnhanced Data Rates for GSM EvolutionNode (physics)Artificial intelligenceSocial network (sociolinguistics)Social mediaData miningWorld Wide WebProgramming languageStructural engineeringPolymer chemistryChemistryEngineeringAdvanced Graph Neural NetworksComplex Network Analysis TechniquesTopic Modeling