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Graph Classification and Clustering Based on Vector Space Embedding/ by Kaspar Riesen , Horst Bunke

By: Contributor(s): Material type: TextTextPublication details: Singapore: World Scientific Publishing Company, 2010.Description: 348 pISBN:
  • 9789814304719
Subject(s): Other classification:
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Holdings
Item type Current library Home library Collection Call number Status Date due Barcode
Book Book Dept. of Futures Studies General Stacks Dept. of Futures Studies Non-fiction 006.4 RIE (Browse shelf(Opens below)) Available DFS4521


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.

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