2023/05/14 by Loïck Lhote, Lhote, Loïck, Béatrice Markhoff +3
Computer Science · #Advanced Graph Neural Networks #Artificial Intelligence (cs.AI) #Cognitive Computing and Networks #FOS: Computer and information sciences #Semantic Web and Ontologies
paper · pdf · doi:10.48550/arxiv.2305.08116
openalex publication_date 2023/05/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Large knowledge graphs combine human knowledge garnered from projects ranging from academia and institutions to enterprises and crowdsourcing. Within such graphs, each relationship between two nodes represents a basic fact involving these two entities. The diversity of the semantics of relationships constitutes the richness of knowledge graphs, leading to the emergence of singular topologies, sometimes chaotic in appearance. However, this complex characteristic can be modeled in a simple way by introducing the concept of superficiality, which controls the overlap between relationships whose facts are generated independently. With this model, superficiality also regulates the balance of the global distribution of knowledge by determining the proportion of misdescribed entities. This is the first model for the structure and dynamics of knowledge graphs. It leads to a better understanding of formal knowledge acquisition and organization.