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V2V: Vector Embedding of a Graph and Applications
2018
2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)
We present V2V, a method for embedding each vertex in a graph as a vector in a fixed dimensional space. Inspired by methods for word embedding such as word2vec, a vertex embedding is computed through enumerating random walks in the graph, and using the resulting vertex sequences to provide the context for each vertex. This embedding allows one to use well-developed techniques from machine learning to solve graph problems such as community detection, graph visualization, and vertex label
doi:10.1109/ipdpsw.2018.00182
dblp:conf/ipps/NguyenT18
fatcat:5ipfrsafqfautk3amd7nmhly2q