Network2Vec Learning Node Representation Based on Space Mapping in Networks

23 Oct 2019Huang ZhenhuaWang ZhenyuZhang RuiZhao YangyangXie XiaohuiSharad Mehrotra

Complex networks represented as node adjacency matrices constrains the application of machine learning and parallel algorithms. To address this limitation, network embedding (i.e., graph representation) has been intensively studied to learn a fixed-length vector for each node in an embedding space, where the node properties in the original graph are preserved... (read more)

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