Network representation learning systematic review: ancestors and current development state

@article{Amara2021NetworkRL,
  title={Network representation learning systematic review: ancestors and current development state},
  author={Amina Amara and Mohamed Ali Hadj Taieb and Mohamed Benaouicha},
  journal={ArXiv},
  year={2021},
  volume={abs/2109.07583}
}
Real-world information networks are increasingly occurring across various disciplines including online social networks and citation networks. These network data are generally characterized by sparseness, nonlinearity and heterogeneity bringing different challenges to the network analytics task to capture inherent properties from network data. Artificial intelligence and machine learning have been recently leveraged as powerful systems to learn insights from network data and deal with presented… 
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