The Structure and Dynamics of Knowledge Graphs, with Superficiality
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Abstract (arXiv)
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.
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References · 7
- 2014The structure and dynamics of multilayer networkscited by 51
- 2018Scale-free networks are rarecited by 40
- 2013Growing multiplex networkscited by 4
- 2020An Empirical Meta-analysis of the Life Sciences (Linked?) Open Data on the Webcited by 3
- 2013Coevolution and correlated multiplexity in multiplex networkscited by 2
- 2014Efficient Network Generation Under General Preferential Attachmentcited by 2
- 2020A Random Growth Model with any Real or Theoretical Degree Distributioncited by 2
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