Abstract
Structural identity is a concept of symmetry in which network nodes are identified according to the network structure and their relationship to other nodes. Structural identity has been studied in theory and practice over the past decades, but only recently has it been addressed with representational learning techniques. This work presents struc2vec, a novel and flexible framework for learning latent representations for the structural identity of nodes. struc2vec uses a hierarchy to measure node similarity at different scales, and constructs a multilayer graph to encode structural similarities and generate structural context for nodes. Numerical experiments indicate that state-of-the-art techniques for…
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Authors
3Topics & keywords
Topics
Keywords
- Computer science
- Identity (music)
- ENCODE
- Theoretical computer science
- Node (physics)
- Hierarchy
- Context (archaeology)
- Graph
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