Fetching the paper…
Reading the bibliography…
Graph embedding techniques allow to learn high-quality feature vectors from graph structures and are useful in a variety of tasks, from node classification to clustering.
Introduction to graph theory
D. Brent West et al · 1996
Earlier work this paper cites.
Modularity and community structure in networks
M. EJ Newman · 2006
Earlier work this paper cites.
Visualizing data using t-sne
L. van der Maaten and G. Hinton · 2008
Earlier work this paper cites.
Hogwild: A lock-free approach to parallelizing stochastic gradient descent
B. Recht, C. Re, S. Wright, and F. Niu · 2011
Earlier work this paper cites.
Translating embeddings for modeling multi-relational data
A. Bordes, N. Usunier, A. Garcia-Duran, J. Weston, and O. Yakhnenko · 2013
Earlier work this paper cites.
Distributed representations of words and phrases and their compositionality
T. Mikolov, I. Sutskever, K. Chen, G. S Corrado, and J. Dean · 2013
Earlier work this paper cites.
Deepwalk: Online learning of social representations
B. Perozzi, R. Al-Rfou, and S. Skiena · 2014
Cited alongside, same era.
Line: Large-scale information network embedding
J. Tang, M. Qu, M. Wang, M. Zhang, J. Yan, and Q. Mei · 2015
Cited alongside, same era.
node2vec: Scalable feature learning for networks
A. Grover and J. Leskovec · 2016
Cited alongside, same era.
Rdf2vec: Rdf graph embeddings for data mining
P. Ristoski and H. Paulheim · 2016
Cited alongside, same era.
Participatory cultural mapping based on collective behavior data in location-based social networks
D. Yang, D. Zhang, and B. Qu · 2016
Cited alongside, same era.
metapath2vec: Scalable representation learning for heterogeneous networks
X. Dong, N. V Chawla, and A. Swami · 2017
Hin2vec: Explore meta-paths in heterogeneous information networks for representation learning
T.-Y. Fu, W.-C. Lee, and Z. Lei · 2017
Later among the works it cites.
Heterogeneous information network embedding for meta path based proximity
Z. Huang and N. Mamoulis · 2017
Later among the works it cites.
Regularizing knowledge graph embeddings via equivalence and inversion axioms
P. Minervini, L. Costabello, E. Muñoz, V. Nováček, and P.-Y. Vandenbussche · 2017
Later among the works it cites.
Knowledge graph embedding: A survey of approaches and applications
Q. Wang, Z. Mao, B. Wang, and L. Guo · 2017
Later among the works it cites.
A comprehensive survey of graph embedding: Problems, techniques, and applications
H. Cai, V. W Zheng, and K. C.-C. Chang · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Centrality measures based on current flow
U. Brandes and D. Fleischer
Cited in the paper.
Building relatedness explanations from knowledge graphs
G. Pirrò
Cited in the paper.
Are meta-paths necessary?: Revisiting heterogeneous graph embeddings
R. Hussein, D. Yang, and P. Cudré-Mauroux · 2018
Later among the works it cites.