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SynGraphy: Succinct Summarisation of Large Networks via Small Synthetic Representative Graphs
In this paper we take the problem of visualising large graphs from a novel perspective: we leave the original graph's nodes and edges behind, and instead summarise its properties such as the clustering coefficient and bipartivity by generating a completely new graph whose structural properties match that of the original graph.
Triple2Vec: Learning Triple Embeddings from Knowledge Graphs
We show that directly applying existing embedding techniques on the nodes of the line graph to learn edge embeddings is not enough in the context of knowledge graphs.
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