Embedding of Graphs with discrete Attributes via Label frequencies

@article{Gibert2013EmbeddingOG,
  title={Embedding of Graphs with discrete Attributes via Label frequencies},
  author={Jaume Gibert and Ernest Valveny and Horst Bunke},
  journal={Int. J. Pattern Recognit. Artif. Intell.},
  year={2013},
  volume={27}
}
Graph-based representations of patterns are very flexible and powerful, but they are not easily processed due to the lack of learning algorithms in the domain of graphs. Embedding a graph into a vector space solves this problem since graphs are turned into feature vectors and thus all the statistical learning machinery becomes available for graph input patterns. In this work we present a new way of embedding discrete attributed graphs into vector spaces using node and edge label frequencies… 

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