[PDF.16ql] Graph Classification and Clustering Based on Vector Space Embedding (Series in Machine Perception and Artificial Intelligence) (Series in Machine Perception and Artifical Intelligence)

Graph Classification and Clustering Based on Vector Space Embedding (Series in Machine Perception and Artificial Intelligence) (Series in Machine Perception and Artifical Intelligence)

[PDF.ej83] Graph Classification and Clustering Based on Vector Space Embedding (Series in Machine Perception and Artificial Intelligence) (Series in Machine Perception and Artifical Intelligence)

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 | #6241099 in Books |  2010-04-29 | Original language:English | PDF # 1 |  9.00 x.90 x6.20l,1.40 | File type: PDF | 348 pages

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|| |It is recommended for the data mining community working on graphs. --Mathematical s|From the Inside Flap|This book is concerned with a fundamentally novel approach to graph-based pattern recognition based on

This book is concerned with a fundamentally novel approach to graph-based pattern recognition based on vector space embedding of graphs. It aims at condensing the high representational power of graphs into a computationally efficient and mathematically convenient feature vector.

This volume utilizes the dissimilarity space representation originally proposed by Duin and Pekalska to embed graphs in real vector spaces. Such an embedding gives one access to all algorithm...

You can specify the type of files you want, for your gadget.Graph Classification and Clustering Based on Vector Space Embedding (Series in Machine Perception and Artificial Intelligence) (Series in Machine Perception and Artifical Intelligence)   |  Kaspar Riesen, Horst Bunke. Just read it with an open mind because none of us really know.

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