Investigating Extensions to Random Walk Based Graph Embedding

17 Feb 2020Joerg SchloettererMartin WehkingFatemeh Salehi RiziMichael Granitzer

Graph embedding has recently gained momentum in the research community, in particular after the introduction of random walk and neural network based approaches. However, most of the embedding approaches focus on representing the local neighborhood of nodes and fail to capture the global graph structure, i.e. to retain the relations to distant nodes... (read more)

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