GraRep: Learning Graph Representations with Global Structural Information

In this paper, we present {GraRep}, a novel model for learning vertex representations of weighted graphs. This model learns low dimensional vectors to represent vertices appearing in a graph and, unlike existing work, integrates global structural information of the graph into the learning process... (read more)

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Datasets


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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK BENCHMARK
Node Classification 20NEWS GraRep Accuracy 81.44 # 1
Node Classification BlogCatalog GraRep Macro-F1 0.3093 # 1

Methods used in the Paper


METHOD TYPE
GraRep
Graph Embeddings
DeepWalk
Graph Embeddings