東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Graph classification and clustering ...

Riesen, Kaspar.{me_controlnum}

Linked to FindBook

Google Book

Amazon

博客來

Graph classification and clustering based on vector space embedding

Record Type:	Electronic resources : Monograph/item
Title/Author:	Graph classification and clustering based on vector space embedding/ Kaspar Riesen & Horst Bunke.
Author:	Riesen, Kaspar.{me_controlnum}
other author:	Bunke, Horst.
Published:	Singapore ;World Scientific Pub. Co., : c2010.,
Description:	xiv, 331 p. :ill.
Subject:	Optical pattern recognition. -
Online resource:	http://www.worldscientific.com/worldscibooks/10.1142/7731#t=toc
ISBN:	9789814304726 (electronic bk.)

Graph classification and clustering based on vector space embedding
Riesen, Kaspar.{me_controlnum}

Graph classification and clustering based on vector space embedding[electronic resource] /Kaspar Riesen & Horst Bunke. - Singapore ;World Scientific Pub. Co.,c2010. - xiv, 331 p. :ill. - Series in machine perception and artificial intelligence ;v. 77. - Series in machine perception and artificial intelligence ;v. 74..

Includes bibliographical references (p. 309-328) and index.

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.

Electronic reproduction.
Singapore :
World Scientific Publishing Co.,
2010.

System requirements: Adobe Acrobat Reader.

ISBN: 9789814304726 (electronic bk.)Subjects--Topical Terms:

665526
Optical pattern recognition.

LC Class. No.: TA1650

Dewey Class. No.: 006.42

Graph classification and clustering based on vector space embedding
LDR:01754nmm a2200277 a 4500 001 1295043
003 WSP
005 20101028141704.0
006 m d
007 cr cuu|||uu|||
008 121114s2010 si a sb 001 0 eng d
020 $a 9789814304726 (electronic bk.)
020 $z 9789814304719
020 $z 9814304719
035 $a 00001066
050 4 $a TA1650
082 0 4 $a 006.42 $2 22
100 1 $a Riesen, Kaspar.{me_controlnum} $3 1572962
245 1 0 $a Graph classification and clustering based on vector space embedding $h [electronic resource] / $c Kaspar Riesen & Horst Bunke.
260 $a Singapore ; $a Hackensack, N.J. : $b World Scientific Pub. Co., $c c2010.
300 $a xiv, 331 p. : $b ill.
490 1 $a Series in machine perception and artificial intelligence ; $v v. 77
504 $a Includes bibliographical references (p. 309-328) and index.
520 $a 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.
533 $a Electronic reproduction. $b Singapore : $c World Scientific Publishing Co., $d 2010. $n System requirements: Adobe Acrobat Reader. $n Mode of access: World Wide Web. $n Available to subscribing institutions.
650 0 $a Optical pattern recognition. $3 665526
650 0 $a Artificial intelligence $x Graphic methods. $3 1572963
650 0 $a Vector spaces. $3 544240
700 1 $a Bunke, Horst. $3 805508
710 2 $a World Scientific (Firm) $3 560950
776 1 $z 9789814304719
776 1 $z 9814304719
830 0 $a Series in machine perception and artificial intelligence ; $v v. 74. $3 1572858
856 4 0 $u http://www.worldscientific.com/worldscibooks/10.1142/7731#t=toc