Capturing Edge Attributes via Network Embedding
Abstract
Network embedding, which aims to learn low-dimensional representations of nodes, has been used for various graph related tasks including visualization, link prediction and node classification. Most existing embedding methods rely solely on network structure. However, in practice we often have auxiliary information about the nodes and/or their interactions, e.g., content of scientific papers in co-authorship networks, or topics of communication...
Paper Details
Title
Capturing Edge Attributes via Network Embedding
Published Date
May 8, 2018
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