331 S. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. Ex-library with stamp and library-signature. GOOD condition, some traces of use. M16039 9789814304719 Sprache: Englisch Gewicht in Gramm: 700.

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Bibliographic Details

Title

Graph classification and clustering based on vector space embedding. Series in machine perception and artificial intelligence; v. 77.

Publisher

Singapore, World Scientific Pub. Co

Publication Date

2010

Language

English

ISBN 10

9814304719

ISBN 13

9789814304719

Binding

Hardcover

Condition

Gut

Weight

700 grams

Seller catalogs

AA Varia

About this title

Synopsis

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.

From the Back Cover

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.

"About this title" may belong to another edition of this title.

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