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

346 Pages·2010·10.679 MB·English
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by Kaspar Riesen, Horst Bunke| 2010| 346 pages| 10.679| English

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

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 algorithms developed in the past for feature vectors, which has been the predominant representation formalism in pattern recognition and related areas for a long time.

Detailed Information

Author:Kaspar Riesen, Horst Bunke
Publication Year:2010
ISBN:9789814304719
Pages:346
Language:English
File Size:10.679
Format:PDF
Price:FREE
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Most books are stored in the elastic cloud where traffic is expensive. For this reason, we have a limit on daily download.